BlinkID SDK enables scanning of over 500 international identity documents, including driving licenses, national identity cards, passports, and others. SDK includes:
- Real-time data and document photo extraction using on-device Machine Learning
- Offline, on-device processing for maximum security and privacy
- Front and back side data capture and comparison
- A beautiful and frictionless scanning UX
- Layered API, allowing everything from simple integration to complex UX customizations.
To quickly integrate the SDK into your app, follow our Quick Start guide.
If you'd like to try BlinkID without coding, simply download the free Microblink Vision demo app:
- Requirements
- Quick Start
- Advanced BlinkID integration instructions
MBRecognizer
and available recognizers- List of available recognizers
- Troubleshooting
- Additional info
SDK package contains Microblink framework and one or more sample apps which demonstrate framework integration. The framework can be deployed in iOS 8.0 or later, iPhone 4S or newer and iPad 2 or newer.
SDK performs significantly better when the images obtained from the camera are focused. Because of that, the SDK can have lower performance on iPad 2 and iPod Touch 4th gen devices, which don't have camera with autofocus.
This Quick Start guide will get you up and performing OCR scanning as quickly as possible. All steps described in this guide are required for the integration.
This guide sets up basic Raw OCR parsing and price parsing at the same time. It closely follows the BlinkOCR-sample app. We highly recommend you try to run the sample app. The sample app should compile and run on your device, and in the iOS Simulator.
The source code of the sample app can be used as the reference during the integration.
- If you wish to use version v1.2.0 or above, you need to install Git Large File Storage by running these comamnds:
brew install git-lfs
git lfs install
-
Be sure to restart your console after installing Git LFS
-
Note: if you already did try adding SDK using cocoapods and it's not working, first install the git-lfs and then clear you cocoapods cache. This should be sufficient to force cocoapods to clone BlinkID SDK, if it still doesn't work, try deinitializing your pods and installing them again.
-
Project dependencies to be managed by CocoaPods are specified in a file called
Podfile
. Create this file in the same directory as your Xcode project (.xcodeproj
) file. -
If you don't have podfile initialized run the following in your project directory.
pod init
- Copy and paste the following lines into the TextEdit window:
platform :ios, '8.0'
target 'Your-App-Name' do
pod 'PPBlinkID', '~> 5.5.0'
end
- Install the dependencies in your project:
$ pod install
- From now on, be sure to always open the generated Xcode workspace (
.xcworkspace
) instead of the project file when building your project:
open <YourProjectName>.xcworkspace
-Download latest release (Download .zip or .tar.gz file starting with BlinkID. DO NOT download Source Code as GitHub does not fully support Git LFS)
OR
Clone this git repository:
- If you wish to clone version v1.4.0 or above, you need to install Git Large File Storage by running these comamnds:
brew install git-lfs
git lfs install
-
Be sure to restart your console after installing Git LFS
-
To clone, run the following shell command:
git clone [email protected]:BlinkID/blinkid-ios.git
-
Copy Microblink.framework and Microblink.bundle to your project folder.
-
In your Xcode project, open the Project navigator. Drag the Microblink.framework and Microblink.bundle files to your project, ideally in the Frameworks group, together with other frameworks you're using. When asked, choose "Create groups", instead of the "Create folder references" option.
- Since Microblink.framework is a dynamic framework, you also need to add it to embedded binaries section in General settings of your target and choose option
Embed & Sign
.
-
Include the additional frameworks and libraries into your project in the "Linked frameworks and libraries" section of your target settings.
- AudioToolbox.framework
- AVFoundation.framework
- CoreMedia.framework
- libc++.tbd
- libiconv.tbd
- libz.tbd
In files in which you want to use scanning functionality place import directive.
Swift
import Microblink
Objective-C
#import <Microblink/Microblink.h>
To initiate the scanning process, first decide where in your app you want to add scanning functionality. Usually, users of the scanning library have a button which, when tapped, starts the scanning process. Initialization code is then placed in touch handler for that button. Here we're listing the initialization code as it looks in a touch handler method.
Also, for initialization purposes, the ViewController which initiates the scan have private properties for MBRawParser
, MBParserGroupProcessor
and MBBlinkInputRecognizer
, so we know how to obtain result.
Swift
class ViewController: UIViewController, MBBlinkIdOverlayViewControllerDelegate {
var blinkIdRecognizer : MBBlinkIdRecognizer?
override func viewDidLoad() {
super.viewDidLoad()
}
@IBAction func didTapScan(_ sender: AnyObject) {
/** Create BlinkID recognizer */
self.blinkIdRecognizer = MBBlinkIdRecognizer()
/** Create BlinkID settings */
let settings : MBBlinkIdOverlaySettings = MBBlinkIdOverlaySettings()
/** Crate recognizer collection */
let recognizerList = [self.blinkIdRecognizer!]
let recognizerCollection : MBRecognizerCollection = MBRecognizerCollection(recognizers: recognizerList)
/** Create your overlay view controller */
let blinkIdOverlayViewController : MBBlinkIdOverlayViewController = MBBlinkIdOverlayViewController(settings: settings, recognizerCollection: recognizerCollection, delegate: self)
/** Create recognizer view controller with wanted overlay view controller */
let recognizerRunneViewController : UIViewController = MBViewControllerFactory.recognizerRunnerViewController(withOverlayViewController: blinkIdOverlayViewController)
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
self.present(recognizerRunneViewController, animated: true, completion: nil)
}
}
Objective-C
@interface ViewController () <MBBlinkIdOverlayViewControllerDelegate>
@property (nonatomic, strong) MBBlinkIdRecognizer *blinkIdRecognizer;
@end
@implementation ViewController
- (void)viewDidLoad {
[super viewDidLoad];
}
- (IBAction)didTapScan:(id)sender {
/** Create BlinkID recognizer */
self.blinkIdRecognizer = [[MBBlinkIdRecognizer alloc] init];
/** Create BlinkID settings */
MBBlinkIdOverlaySettings* settings = [[MBBlinkIdOverlaySettings alloc] init];
/** Create recognizer collection */
MBRecognizerCollection *recognizerCollection = [[MBRecognizerCollection alloc] initWithRecognizers:@[self.blinkIdRecognizer]];
/** Create your overlay view controller */
MBBlinkIdOverlayViewController *blinkIdOverlayViewController = [[MBBlinkIdOverlayViewController alloc] initWithSettings:settings recognizerCollection:recognizerCollection delegate:self];
/** Create recognizer view controller with wanted overlay view controller */
UIViewController<MBRecognizerRunnerViewController>* recognizerRunnerViewController = [MBViewControllerFactory recognizerRunnerViewControllerWithOverlayViewController:blinkIdOverlayViewController];
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
[self presentViewController:recognizerRunnerViewController animated:YES completion:nil];
}
@end
A valid license key is required to initalize scanning. You can generate a free trial license key, after you register, at Microblink developer dashboard.
You can include the license key in your app by passing a string or a file with license key.
Note that you need to set the license key before intializing scanning. Ideally in AppDelegate
or viewDidLoad
before initializing any recognizers.
You can pass the license key as a string, the following way:
Swift
MBMicroblinkSDK.sharedInstance().setLicenseKey("LICENSE-KEY")
Objective-C
[[MBMicroblinkSDK sharedInstance] setLicenseKey:@"LICENSE-KEY"];
Or you can include the license key, with the code below. Please make sure that the file that contains the license key is included in your project and is copied during Copy Bundle Resources build phase.
Swift
MBMicroblinkSDK.sharedInstance().setLicenseResource("license-key-file", withExtension: "txt", inSubdirectory: "directory-to-license-key", for: Bundle.main)
Objective-C
[[MBMicroblinkSDK sharedInstance] setLicenseResource:@"license-key-file" withExtension:@"txt" inSubdirectory:@"" forBundle:[NSBundle mainBundle]];
In the previous step, you instantiated MBDocumentOverlayViewController
object with a delegate object. This object gets notified on certain events in scanning lifecycle. In this example we set it to self
. The protocol which the delegate has to implement is MBDocumentOverlayViewControllerDelegate
protocol. It is necessary to conform to that protocol. We will discuss more about protocols in Advanced integration section. You can use the following default implementation of the protocol to get you started.
Swift
func blinkIdOverlayViewControllerDidFinishScanning(_ blinkIdOverlayViewController: MBBlinkIdOverlayViewController, state: MBRecognizerResultState) {
// this is done on background thread
// check for valid state
if state == .valid {
// first, pause scanning until we process all the results
blinkIdOverlayViewController.recognizerRunnerViewController?.pauseScanning()
DispatchQueue.main.async(execute: {() -> Void in
// All UI interaction needs to be done on main thread
})
}
}
func blinkIdOverlayViewControllerDidTapClose(_ blinkIdOverlayViewController: MBBlinkIdOverlayViewController) {
// Your action on cancel
}
Objective-C
- (void)blinkIdOverlayViewControllerDidFinishScanning:(MBBlinkIdOverlayViewController *)blinkIdOverlayViewController state:(MBRecognizerResultState)state {
// this is done on background thread
// check for valid state
if (state == MBRecognizerResultStateValid) {
// first, pause scanning until we process all the results
[blinkIdOverlayViewController.recognizerRunnerViewController pauseScanning];
dispatch_async(dispatch_get_main_queue(), ^{
// All UI interaction needs to be done on main thread
});
}
}
- (void)blinkIdOverlayViewControllerDidTapClose:(nonnull MBBlinkIdOverlayViewController *)blinkIdOverlayViewController {
// Your action on cancel
}
This section covers more advanced details of BlinkID integration.
- First part will cover the possible customizations when using UI provided by the SDK.
- Second part will describe how to embed
MBRecognizerRunnerViewController's delegates
into yourUIViewController
with the goal of creating a custom UI for scanning, while still using camera management capabilites of the SDK. - Third part will describe how to use the
MBRecognizerRunner
(Direct API) for recognition directly fromUIImage
without the need of camera or to recognize camera frames that are obtained by custom camera management. - Fourth part will describe recognizer concept and available recognizers.
Within BlinkID SDK there are several built-in overlay view controllers and scanning subview overlays that you can use to perform scanning.
MBDocumentOverlayViewController
is overlay view controller best suited for performing scanning of various document cards. It has MBDocumentOverlayViewControllerDelegate
delegate which can be used out-of-the-box to perform scanning using the default UI. Here is an example how to use and initialize MBDocumentOverlayViewController
:
Swift
/** Create your overlay view controller */
let documentOverlayViewController : MBDocumentOverlayViewController = MBDocumentOverlayViewController(settings: documentSettings, recognizerCollection: recognizerCollection, delegate: self)
/** Create recognizer view controller with wanted overlay view controller */
let recognizerRunneViewController : UIViewController = MBViewControllerFactory.recognizerRunnerViewController(withOverlayViewController: documentOverlayViewController)
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
self.present(recognizerRunneViewController, animated: true, completion: nil)
Objective-C
MBDocumentOverlayViewController *overlayVC = [[MBDocumentOverlayViewController alloc] initWithSettings:settings recognizerCollection: recognizerCollection delegate:self];
UIViewController<MBRecognizerRunnerViewController>* recognizerRunnerViewController = [MBViewControllerFactory recognizerRunnerViewControllerWithOverlayViewController:overlayVC];
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
[self presentViewController:recognizerRunnerViewController animated:YES completion:nil];
As you can see, when initializing MBDocumentOverlayViewController
, we are sending delegate property as self
. To get results, we need to conform to MBDocumentOverlayViewControllerDelegate
protocol.
MBDocumentVerificationOverlayViewController
is overlay view controller best suited for performing scanning of various document for both front and back side. It has MBDocumentVerificationOverlayViewControllerDelegate
delegate which can be used out-of-the-box to perform scanning using the default UI. Here is an example how to use and initialize MBDocumentVerificationOverlayViewController
:
Swift
/** Create your overlay view controller */
let documentOverlayViewController : MBDocumentVerificationOverlayViewController = MBDocumentVerificationOverlayViewController(settings: documentVerificationSettings, recognizerCollection: recognizerCollection, delegate: self)
/** Create recognizer view controller with wanted overlay view controller */
let recognizerRunneViewController : UIViewController = MBViewControllerFactory.recognizerRunnerViewController(withOverlayViewController: documentOverlayViewController)
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
self.present(recognizerRunneViewController, animated: true, completion: nil)
Objective-C
MBDocumentVerificationOverlayViewController *overlayVC = [[MBDocumentVerificationOverlayViewController alloc] initWithSettings:settings recognizerCollection: recognizerCollection delegate:self];
UIViewController<MBRecognizerRunnerViewController>* recognizerRunnerViewController = [MBViewControllerFactory recognizerRunnerViewControllerWithOverlayViewController:overlayVC];
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
[self presentViewController:recognizerRunnerViewController animated:YES completion:nil];
As you can see, when initializing MBDocumentVerificationOverlayViewController
, we are sending delegate property as self
. To get results, we need to conform to MBDocumentVerificationOverlayViewControllerDelegate
protocol.
MBBlinkIdOverlayViewController
implements new UI for scanning identity documents, which is optimally designed to be used with new MBBlinkIdRecognizer
and MBBlinkIdCombinedRecognizer
. The new MBBlinkIdOverlayViewController
implements several new features:
- clear indication for searching phase, when BlinkID is searching for an ID document
- clear progress indication, when BlinkID is busy with OCR and data extraction
- clear message when the document is not supported
- visual indications when the user needs to place the document closer to the camera
- when
MBBlinkIdCombinedRecognizer
is used, visual indication that the data from the front side of the document doesn't match the data on the back side of the document.
The new UI allows the user to scan the document at an any angle, in any orientation. We recommend forcing landscape orientation if you scan barcodes on the back side, because in that orientation success rate will be higher. To force the UI in landscape mode, use the following instructions:
Swift
let settings = MBBlinkIdOverlaySettings()
settings.autorotateOverlay = true
settings.supportedOrientations = UIInterfaceOrientationMask.landscape
Objective-C
MBBlinkIdOverlaySettings *settings = [[MBBlinkIdOverlaySettings alloc] init];
settings.autorotateOverlay = YES;
settings.supportedOrientations = UIInterfaceOrientationMaskLandscape;
It has MBBlinkIdOverlayViewControllerDelegate
delegate which can be used out-of-the-box to perform scanning using the default UI. Here is an example how to use and initialize MBBlinkIdOverlayViewController
:
Swift
/** Create your overlay view controller */
let blinkIdOverlayViewController : MBBlinkIdOverlayViewController = MBBlinkIdOverlayViewController(settings: blinkIdSettings, recognizerCollection: recognizerCollection, delegate: self)
/** Create recognizer view controller with wanted overlay view controller */
let recognizerRunneViewController : UIViewController = MBViewControllerFactory.recognizerRunnerViewController(withOverlayViewController: blinkIdOverlayViewController)
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
self.present(recognizerRunneViewController, animated: true, completion: nil)
Objective-C
MBBlinkIdOverlayViewController *overlayVC = [[MBBlinkIdOverlayViewController alloc] initWithSettings:settings recognizerCollection: recognizerCollection delegate:self];
UIViewController<MBRecognizerRunnerViewController>* recognizerRunnerViewController = [MBViewControllerFactory recognizerRunnerViewControllerWithOverlayViewController:overlayVC];
/** Present the recognizer runner view controller. You can use other presentation methods as well (instead of presentViewController) */
[self presentViewController:recognizerRunnerViewController animated:YES completion:nil];
As you can see, when initializing MBBlinkIdOverlayViewController
, we are sending delegate property as self
. To get results, we need to conform to MBBlinkIdOverlayViewControllerDelegate
protocol.
Please check our Samples for custom implementation of overlay view controller.
Overlay View Controller is an abstract class for all overlay views.
It's responsibility is to provide meaningful and useful interface for the user to interact with.
Typical actions which need to be allowed to the user are:
- intuitive and meaniningful way to guide the user through scanning process. This is usually done by presenting a "viewfinder" in which the user need to place the scanned object
- a way to cancel the scanning, typically with a "cancel" or "back" button
- a way to power on and off the light (i.e. "torch") button
BlinkID SDK always provides it's own default implementation of the Overlay View Controller for every specific use. Your implementation should closely mimic the default implementation as it's the result of thorough testing with end users. Also, it closely matches the underlying scanning technology.
For example, the scanning technology usually gives results very fast after the user places the device's camera in the expected way above the scanned object. This means a progress bar for the scan is not particularly useful to the user. The majority of time the user spends on positioning the device's camera correctly. That's just an example which demonstrates careful decision making behind default camera overlay view.
To use your custom overlay with Microblink's camera view, you must first subclass MBCustomOverlayViewController
and implement the overlay behaviour conforming wanted protocols.
There are five MBRecognizerRunnerViewController
protocols and one overlay protocol MBOverlayViewControllerInterface
.
Five RecognizerRunnerView
protocols are:
MBScanningRecognizerRunnerViewControllerDelegate
MBDetectionRecognizerRunnerViewControllerDelegate
MBOcrRecognizerRunnerViewControllerDelegate
MBDebugRecognizerRunnerViewControllerDelegate
MBRecognizerRunnerViewControllerDelegate
In viewDidLoad
, other protocol conformation can be done and it's done on recognizerRunnerViewController
property of MBOverlayViewController
, for example:
Swift and Objective-C
self.scanningRecognizerRunnerViewControllerDelegate = self;
The SDK contains various subviews you can use to notify users of the state of scanning. If you want to use built-in implementation we recommend to use MBModernViewfinderSubview
. In can be initialized in viewDidLoad
method:
Swift
viewfinderSubview = MBModernViewfinderSubview()
viewfinderSubview.frame = view.frame
viewfinderSubview.moveable = true
view.addSubview(viewfinderSubview)
Objective-C
self.viewfinderSubview = [[MBModernViewfinderSubview alloc] init];
self.viewfinderSubview.frame = self.view.frame;
self.viewfinderSubview.delegate = self.overlaySubviewsDelegate;
self.viewfinderSubview.moveable = YES;
[self.view addSubview:self.viewfinderSubview];
To use this subview you'll need to implement MBDetectionRecognizerRunnerViewControllerDelegate
(http://blinkid.github.io/blinkid-ios/Protocols/MBDetectionRecognizerRunnerViewControllerDelegate.html) then in the -recognizerRunnerViewController:didFinishDetectionWithDisplayableQuad:
notify subview of detection changes.
Swift
func recognizerRunnerViewController(_ recognizerRunnerViewController: Any!, didFinishDetectionWithDisplayableQuad displayableQuad: MBDisplayableQuadDetection) {
viewfinderSubview.detectionFinished(withDisplayableQuad: displayableQuad)
}
Objective-C
- (void)recognizerRunnerViewController: (nonnull UIViewController<MBRecognizerRunnerViewController> *) recognizerRunnerViewController didFinishDetectionWithDisplayableQuad: (nonnull MBDisplayableQuadDetection *)displayableQuad {
[self.viewfinderSubview detectionFinishedWithDisplayableQuad:displayableQuad];
}
In Quick Start guide it is shown how to use a default overlay view controller. You can now swap default view controller with your implementation of CustomOverlayViewController
Swift
let recognizerRunnerViewController : UIViewController = MBViewControllerFactory.recognizerRunnerViewController(withOverlayViewController: CustomOverlayViewController)
Objective-C
UIViewController<MBRecognizerRunnerViewController>* recognizerRunnerViewController = [MBViewControllerFactory recognizerRunnerViewControllerWithOverlayViewController:CustomOverlayViewController];
This guide will in short present you how to process UIImage objects with BlinkID SDK, without starting the camera video capture.
With this feature you can solve various use cases like: - recognizing text on images in Camera roll - taking full resolution photo and sending it to processing - scanning barcodes on images in e-mail etc.
DirectAPI-sample demo app here will present UIImagePickerController for taking full resolution photos, and then process it with Microblink SDK to get scanning results using Direct processing API.
Direct processing API is handled with MBRecognizerRunner
. That is a class that handles processing of images. It also has protocols as MBRecognizerRunnerViewController
.
Developer can choose which protocol to conform:
MBScanningRecognizerRunnerDelegate
MBDetectionRecognizerRunnerDelegate
MBDebugRecognizerRunnerDelegate
MBOcrRecognizerRunnerDelegate
In example, we are conforming to MBScanningRecognizerRunnerDelegate
protocol.
To initiate the scanning process, first decide where in your app you want to add scanning functionality. Usually, users of the scanning library have a button which, when tapped, starts the scanning process. Initialization code is then placed in touch handler for that button. Here we're listing the initialization code as it looks in a touch handler method.
Swift
func setupRecognizerRunner() {
var recognizers = [MBRecognizer]()
pdf417Recognizer = MBPdf417Recognizer()
recognizers.append(pdf417Recognizer!)
let recognizerCollection = MBRecognizerCollection(recognizers: recognizers)
recognizerRunner = MBRecognizerRunner(recognizerCollection: recognizerCollection)
recognizerRunner?.scanningRecognizerRunnerDelegate = self
}
func processImageRunner(_ originalImage: UIImage) {
var image: MBImage? = nil
if let anImage = originalImage {
image = MBImage(uiImage: anImage)
}
image?.cameraFrame = true
image?.orientation = MBProcessingOrientation.left
let _serialQueue = DispatchQueue(label: "com.microblink.DirectAPI-sample-swift")
_serialQueue.async(execute: {() -> Void in
self.recognizerRunner?.processImage(image!)
})
}
func recognizerRunner(_ recognizerRunner: MBRecognizerRunner, didFinishScanningWith state: MBRecognizerResultState) {
if blinkInputRecognizer.result.resultState == MBRecognizerResultStateValid {
// Handle result
}
}
Objective-C
- (void)setupRecognizerRunner {
NSMutableArray<MBRecognizer *> *recognizers = [[NSMutableArray alloc] init];
self.pdf417Recognizer = [[MBPdf417Recognizer alloc] init];
[recognizers addObject: self.pdf417Recognizer];
MBRecognizerCollection *recognizerCollection = [[MBRecognizerCollection alloc] initWithRecognizers:recognizers];
self.recognizerRunner = [[MBRecognizerRunner alloc] initWithRecognizerCollection:recognizerCollection];
self.recognizerRunner.scanningRecognizerRunnerDelegate = self;
}
- (void)processImageRunner:(UIImage *)originalImage {
MBImage *image = [MBImage imageWithUIImage:originalImage];
image.cameraFrame = YES;
image.orientation = MBProcessingOrientationLeft;
dispatch_queue_t _serialQueue = dispatch_queue_create("com.microblink.DirectAPI-sample", DISPATCH_QUEUE_SERIAL);
dispatch_async(_serialQueue, ^{
[self.recognizerRunner processImage:image];
});
}
- (void)recognizerRunner:(nonnull MBRecognizerRunner *)recognizerRunner didFinishScanningWithState:(MBRecognizerResultState)state {
if (self.blinkInputRecognizer.result.resultState == MBRecognizerResultStateValid) {
// Handle result
}
}
Now you've seen how to implement the Direct processing API.
In essence, this API consists of two steps:
- Initialization of the scanner.
- Call of
- (void)processImage:(MBImage *)image;
method for each UIImage or CMSampleBufferRef you have.
Some recognizers support recognition from NSString
. They can be used through Direct API to parse given NSString
and return data just like when they are used on an input image. When recognition is performed on NSString
, there is no need for the OCR. Input NSString
is used in the same way as the OCR output is used when image is being recognized.
Recognition from String
can be performed in the same way as recognition from image.
The only difference is that user should call - (void)processString:(NSString *)string;
on MBRecognizerRunner
.
The MBRecognizer
is the basic unit of processing within the SDK. Its main purpose is to process the image and extract meaningful information from it. As you will see later, the SDK has lots of different MBRecognizer
objects that have various purposes.
Each MBRecognizer
has a MBRecognizerResult
object, which contains the data that was extracted from the image. The MBRecognizerResult
object is a member of corresponding MBRecognizer
object its lifetime is bound to the lifetime of its parent MBRecognizer
object. If you need your MBRecognizerRecognizer
object to outlive its parent MBRecognizer
object, you must make a copy of it by calling its method copy
.
While MBRecognizer
object works, it changes its internal state and its result. The MBRecognizer
object's MBRecognizerResult
always starts in Empty
state. When corresponding MBRecognizer
object performs the recognition of given image, its MBRecognizerResult
can either stay in Empty
state (in case MBRecognizer
failed to perform recognition), move to Uncertain
state (in case MBRecognizer
performed the recognition, but not all mandatory information was extracted) or move to Valid
state (in case MBRecognizer
performed recognition and all mandatory information was successfully extracted from the image).
As soon as one MBRecognizer
object's MBRecognizerResult
within MBRecognizerCollection
given to MBRecognizerRunner
or MBRecognizerRunnerViewController
changes to Valid
state, the onScanningFinished
callback will be invoked on same thread that performs the background processing and you will have the opportunity to inspect each of your MBRecognizer
objects' MBRecognizerResult
to see which one has moved to Valid
state.
As soon as onScanningFinished
method ends, the MBRecognizerRunnerViewController
will continue processing new camera frames with same MBRecognizer
objects, unless paused
. Continuation of processing or reset
recognition will modify or reset all MBRecognizer
objects's MBRecognizerResult
. When using built-in activities, as soon as onScanningFinished
is invoked, built-in activity pauses the MBRecognizerRunnerViewController
and starts finishing the activity, while saving the MBRecognizerCollection
with active MBRecognizer
.
The MBRecognizerCollection
is is wrapper around MBRecognizer
objects that has array of MBRecognizer
objects that can be used to give MBRecognizer
objects to MBRecognizerRunner
or MBRecognizerRunnerViewController
for processing.
The MBRecognizerCollection
is always constructed with array [[MBRecognizerCollection alloc] initWithRecognizers:recognizers]
of MBRecognizer
objects that need to be prepared for recognition (i.e. their properties must be tweaked already).
The MBRecognizerCollection
manages a chain of MBRecognizer
objects within the recognition process. When a new image arrives, it is processed by the first MBRecognizer
in chain, then by the second and so on, iterating until a MBRecognizer
object's MBRecognizerResult
changes its state to Valid
or all of the MBRecognizer
objects in chain were invoked (none getting a Valid
result state).
You cannot change the order of the MBRecognizer
objects within the chain - no matter the order in which you give MBRecognizer
objects to MBRecognizerCollection
, they are internally ordered in a way that provides best possible performance and accuracy. Also, in order for SDK to be able to order MBRecognizer
objects in recognition chain in a best way possible, it is not allowed to have multiple instances of MBRecognizer
objects of the same type within the chain. Attempting to do so will crash your application.
This section will give a list of all MBRecognizer
objects that are available within BlinkID SDK, their purpose and recommendations how they should be used to get best performance and user experience.
The MBFrameGrabberRecognizer
is the simplest recognizer in SDK, as it does not perform any processing on the given image, instead it just returns that image back to its onFrameAvailable
. Its result never changes state from empty.
This recognizer is best for easy capturing of camera frames with MBRecognizerRunnerViewController
. Note that MBImage
sent to onFrameAvailable
are temporary and their internal buffers all valid only until the onFrameAvailable
method is executing - as soon as method ends, all internal buffers of MBImage
object are disposed. If you need to store MBImage
object for later use, you must create a copy of it by calling copy
.
The MBSuccessFrameGrabberRecognizer
is a special MBecognizer
that wraps some other MBRecognizer
and impersonates it while processing the image. However, when the MBRecognizer
being impersonated changes its MBRecognizerResult
into Valid
state, the MBSuccessFrameGrabberRecognizer
captures the image and saves it into its own MBSuccessFrameGrabberRecognizerResult
object.
Since MBSuccessFrameGrabberRecognizer
impersonates its slave MBRecognizer
object, it is not possible to give both concrete MBRecognizer
object and MBSuccessFrameGrabberRecognizer
that wraps it to same MBRecognizerCollection
- doing so will have the same result as if you have given two instances of same MBRecognizer
type to the MBRecognizerCollection
- it will crash your application.
This recognizer is best for use cases when you need to capture the exact image that was being processed by some other MBRecognizer
object at the time its MBRecognizerResult
became Valid
. When that happens, MBSuccessFrameGrabberRecognizer's
MBSuccessFrameGrabberRecognizerResult
will also become Valid
and will contain described image.
Unless stated otherwise for concrete recognizer, single side BlinkID recognizes from this list can be used in any context, but they work best with the MBDocumentOverlayViewController
, which has UI best suited for document scanning.
Combined recognizers should be used with MBDocumentVerificationOverlayViewController
which manages scanning of multiple document sides in the single camera opening and guides the user through the scanning process. Some combined recognizers support scanning of multiple document types, but only one document type can be scanned at a time.
The MBMrtdRecognizer
is used for scanning and data extraction from the Machine Readable Zone (MRZ) of the various Machine Readable Travel Documents (MRTDs) like ID cards and passports. This recognizer is not bound to the specific country, but it can be configured to only return data that match some criteria defined by the MBMrzFilter
.
You can find information about usage context at the beginning of this section.
The MBMrtdCombinedRecognizer
scans Machine Readable Zone (MRZ) after scanning the full document image and face image (usually MRZ is on the back side and face image is on the front side of the document). Internally, it uses MBDocumentFaceRecognizer for obtaining full document image and face image as the first step and then MBMrtdRecognizer for scanning the MRZ.
You can find information about usage context at the beginning of this section.
The MBPassportRecognizer
is used for scanning and data extraction from the Machine Readable Zone (MRZ) of the various passport documents. This recognizer also returns face image from the passport.
You can find information about usage context at the beginning of this section.
The MBVisaRecognizer
is used for scanning and data extraction from the Machine Readable Zone (MRZ) of the various visa documents. This recognizer also returns face image from the visa document.
You can find information about usage context at the beginning of this section.
The MBUsdlRecognizer
is used for scanning PDF417 barcode from USA ID cards and driver’s licence, Canadian ID cards and driving licence, and Nigerian driving licence.
You can find information about usage context at the beginning of this section.
The MBUsdlCombinedRecognizer
first scans the front side of the document to obtain the full document image and face image. It then scans PDF417 barcode from the back side of AAMVA standard documents. This includes USA ID cards and driver’s licence, Canadian ID cards and driving licence, and Nigerian driving licence.
Internally, it uses MBDocumentFaceRecognizer for obtaining full document image and face image as the first step and then MBUsdlRecognizer for scanning the PDF417 barcode.
You can find information about usage context at the beginning of this section.
The MBDocumentFaceRecognizer
is a special type of recognizer that only returns face image and full document image of the scanned document. It does not extract document fields like first name, last name, etc. This generic recognizer can be used to obtain document images in cases when specific support for some document type is not available.
You can find information about usage context at the beginning of this section.
The MBBlinkIdRecognizer
scans and extracts data from the front side of the supported document.
You can find the list of the currently supported documents here
.
We will continue expanding this recognizer by adding support for new document types in the future. Star this repo to stay updated.
Use MBBlinkIdCombinedRecognizer
for scanning both sides of the supported document. First, it scans and extracts data from the front, then scans and extracts data from the barcode on the back, and finally, combines results from both sides. The BlinkIDCombinedRecognizer
also performs data matching and returns a flag if the extracted data captured from the front side matches the data from the barcode on the back.
You can find the list of the currently supported documents here
.
We will continue expanding this recognizer by adding support for new document types in the future. Star this repo to stay updated.
In case of problems with integration of the SDK, first make sure that you have tried integrating it into XCode by following integration instructions.
If you have followed XCode integration instructions and are still having integration problems, please contact us at help.microblink.com.
In case of problems with using the SDK, you should do as follows:
If you are getting "invalid licence key" error or having other licence-related problems (e.g. some feature is not enabled that should be or there is a watermark on top of camera), first check the console. All licence-related problems are logged to error log so it is easy to determine what went wrong.
When you have determine what is the licence-relate problem or you simply do not understand the log, you should contact us help.microblink.com. When contacting us, please make sure you provide following information:
- exact Bundle ID of your app (from your
info.plist
file) - licence that is causing problems
- please stress out that you are reporting problem related to iOS version of PDF417.mobi SDK
- if unsure about the problem, you should also provide excerpt from console containing licence error
If you are having problems with scanning certain items, undesired behaviour on specific device(s), crashes inside PDF417.mobi SDK or anything unmentioned, please do as follows:
- Contact us at help.microblink.com describing your problem and provide following information:
- log file obtained in previous step
- high resolution scan/photo of the item that you are trying to scan
- information about device that you are using
- please stress out that you are reporting problem related to iOS version of PDF417.mobi SDK
Here is a list of frequently asked questions and solutions for them and also a list of known problems in the SDK and how to work around them.
In demo everything worked, but after switching to production license I get NSError
with MBMicroblinkSDKRecognizerErrorDomain
and MBRecognizerFailedToInitalize
code as soon as I construct specific MBRecognizer
object
Each license key contains information about which features are allowed to use and which are not. This NSError
indicates that your production license does not allow using of specific MBRecognizer
object. You should contact support to check if provided licence is OK and that it really contains all features that you have purchased.
I get NSError
with MBMicroblinkSDKRecognizerErrorDomain
and MBRecognizerFailedToInitalize
code with trial license key
Whenever you construct any MBRecognizer
object or, a check whether license allows using that object will be performed. If license is not set prior constructing that object, you will get NSError
with MBMicroblinkSDKRecognizerErrorDomain
and MBRecognizerFailedToInitalize
code. We recommend setting license as early as possible in your app.
Make sure you link your app with iconv and Accelerate frameworks as shown in Quick start.
If you are using Cocoapods, please be sure that you've installed git-lfs
prior to installing pods. If you are still getting this error, go to project folder and execute command git-lfs pull
.
In my didFinish
callback I have the result inside my MBRecognizer
, but when scanning activity finishes, the result is gone
This usually happens when using MBRecognizerRunnerViewController
and forgetting to pause the MBRecognizerRunnerViewController
in your didFinish
callback. Then, as soon as didFinish
happens, the result is mutated or reset by additional processing that MBRecognizer
performs in the time between end of your didFinish
callback and actual finishing of the scanning activity. For more information about statefulness of the MBRecognizer
objects, check this section.
Microblink.framework is a dynamic framework which contains slices for all architectures - device and simulator. If you intend to extract .ipa file for ad hoc distribution, you'll need to preprocess the framework to remove simulator architectures.
Ideal solution is to add a build phase after embed frameworks build phase, which strips unused slices from embedded frameworks.
Build step is based on the one provided here: http://ikennd.ac/blog/2015/02/stripping-unwanted-architectures-from-dynamic-libraries-in-xcode/
APP_PATH="${TARGET_BUILD_DIR}/${WRAPPER_NAME}"
# This script loops through the frameworks embedded in the application and
# removes unused architectures.
find "$APP_PATH" -name '*.framework' -type d | while read -r FRAMEWORK
do
FRAMEWORK_EXECUTABLE_NAME=$(defaults read "$FRAMEWORK/Info.plist" CFBundleExecutable)
FRAMEWORK_EXECUTABLE_PATH="$FRAMEWORK/$FRAMEWORK_EXECUTABLE_NAME"
echo "Executable is $FRAMEWORK_EXECUTABLE_PATH"
EXTRACTED_ARCHS=()
for ARCH in $ARCHS
do
echo "Extracting $ARCH from $FRAMEWORK_EXECUTABLE_NAME"
lipo -extract "$ARCH" "$FRAMEWORK_EXECUTABLE_PATH" -o "$FRAMEWORK_EXECUTABLE_PATH-$ARCH"
EXTRACTED_ARCHS+=("$FRAMEWORK_EXECUTABLE_PATH-$ARCH")
done
echo "Merging extracted architectures: ${ARCHS}"
lipo -o "$FRAMEWORK_EXECUTABLE_PATH-merged" -create "${EXTRACTED_ARCHS[@]}"
rm "${EXTRACTED_ARCHS[@]}"
echo "Replacing original executable with thinned version"
rm "$FRAMEWORK_EXECUTABLE_PATH"
mv "$FRAMEWORK_EXECUTABLE_PATH-merged" "$FRAMEWORK_EXECUTABLE_PATH"
done
Complete API reference can be found here.
For any other questions, feel free to contact us at help.microblink.com.