Acuant iOS Mobile SDK v10 [DEPRECATED]

Last updated – April 9, 2019

Copyright ^© 2003-2018 Acuant Inc. All rights reserved.

This document contains proprietary and confidential information and creative works owned by Acuant and its respective licensors, if any. Any use, copying, publication, distribution, display, modification, or transmission of such technology in whole or in part in any form or by any means without the prior express written permission of Acuant is strictly prohibited. Except where expressly provided by Acuant in writing, possession of this information shall not be construed to confer any license or rights under any Acuant intellectual property rights, whether by estoppel, implication, or otherwise.

AssureID and i-Dentify are trademarks of Acuant Inc. Other Acuant product or service names or logos referenced this document are either trademarks or registered trademarks of Acuant.

All 3M trademarks are trademarks of Gemalto Inc.

Windows^® is a registered trademark of Microsoft Corporation.

Certain product, service, or company designations for companies other than Acuant may be mentioned in this document for identification purposes only. Such designations are often claimed as trademarks or service marks. In all instances where Acuant is aware of a claim, the designation appears in initial capital or all capital letters. However, you should contact the appropriate companies for more complete information regarding such designations and their registration status.

April 2019

Acuant Inc.

6080 Center Drive, Suite 850

Los Angeles, CA 90045

==================

License

This software is subject to Acuant's end user license agreement (EULA), which can be found here.

Introduction

THIS SDK HAS BEEN DEPRECATED

Acuant Web Services supports data extraction from driver’s licenses, state IDs, other government issued IDs, custom IDs, driver’s licenses, barcodes, and passports. It also supports document authentication and facial recognition to verify and authenticate the identity.

This document contains a detailed description of all functions that developers need to integrate with the Acuant iOS Mobile SDK.

Setup

Prerequisites: iOS version 11.0 or higher.

1. Add the Acuant iOS SDK embeded framework:

   

Initializing the SDK

1. Set the endpoints:

   let endPoints = Endpoints()
   endPoints.frmEndpoint = "https://frm.acuant.net/api/v1"
   endPoints.idEndpoint = "https://services.assureid.net"
   endPoints.healthInsuranceEndpoint = "https://medicscan.acuant.net/api/v1"
   

2. Set the credentials:

    let credential = Credential()
    credential.endpoints = endPoints
    credential.username = "userid@acuantcorp.com"
    credential.password = "password"
    credential.subscription = "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX"
   

3. Initialize the Controller:

    Controller.initialize(credential: credential, delegate: InitializationDelegate)
    
    // Delegate Call back
    func initializationFinished(error: AcuantError?) {
    		if(error == nil){
        		// Success
    		}else{
        		// Handle error
    		}
    }
   

Capturing an image

Image capture is illustrated in the Sample App in DocumentCameraController.

Note The illustrated capture code is only helpful if there is a requirement to detect PDF417 2D barcode in the image.

// To create a document capture session
   captureSession = Controller.getDocumentCaptureSession(delegate: self,captureDevice: captureDevice)
            
            
// The following method will start detecting barcode on the document with time in seconds.
captureSession.startCapturing(timeout: 2)

// When the capture session is set up the following call back will be called
func didStartCaptureSession()

Cropping an image

After an image is captured, it is sent to the cropping library for cropping.

1. Set card attributes:

   If the card type is known, then set it to the correct type (for example, CardType.ID1, CardType.ID2, or CardType.ID3). If card type is ID2, then set the card width (in inches). If the card type is either ID1 or ID3, then use the AUTO setting to automatically detect the card type with the cropping function.

    let cardAttributes = CardAttributes()
    cardAttributes.cardType = CardType.AUTO
   

Note https://en.wikipedia.org/wiki/ISO/IEC_7810

1. Set the cropping options:

   Set the CardAttributes, regardless of whether the captured image(s) is a Health Insurance card, and whether the Image metrics (Sharpness and Glare) are required.

    let croppingOptions = CroppingOptions()
    croppingOptions.cardAtributes = cardAttributes
    croppingOptions.imageMetricsRequired = true
    // For Medical Card set isHealthCard to true
    croppingOptions.isHealthCard = false
   

2. Set the image to crop:

    let croppingData = CroppingData()
    croppingData.image = image
   

3. Crop the image:

    Controller.crop(options: croppingOptions, data: croppingData)\
   

Image class structure:

	public class Image {
		public var image : UIImage? = nil
		public var detectedCardType : CardType = CardType.ID1
		public var hasImageMetrics : Bool = false
		public var isSharp : Bool = false
		public var hasGlare : Bool = false
		public var sharpnessGrade : Int = 0
		public var glareGrade : Int = 0
		public var error : AcuantError? = nil
	}

Note A sharpness grade of 50 and above is defined as a sharp image. A glare grade of 50 or higher indicates that there is no glare present in the image.

Using facial recognition

The following sample describes how to create a live face capture session.

1. Create a live face capture session and a CameraSource:

    var captureSession = Controller.getFaceCaptureSession
     (delegate: LiveFaceCaptureDelegate,captureDevice:
     captureDevice,previewSize:self.view.layer.bounds.size)
   

2. LiveFaceCaptureDelegate Callback

    func liveFaceDetailsCaptured(liveFaceDetails: LiveFaceDetails?) {
    
    if(liveFaceDetails?.faceRect != nil && liveFaceDetails?.image != nil){
        	if(liveFaceDetails?.isLiveFace)!{
            	// Live face is detected
            	
            	// liveFaceDetails?.image is the face image
        	}
    	}        
    }
    
    public class LiveFaceDetails{
    	public var  isLiveFace : Bool = false
    	public var  faceRect : CGRect? = nil
    	public var cleanAperture : CGRect? = nil
    	public var image : UIImage? = nil
    	public var error : AcuantError? = nil
    }
   

Processing the captured images

Use a Web Service call to process the captured images.

1. Set the processing options:

    let attributes = CardAttributes()
    attributes.cardType = CardType.ID1
    
    let options = IdOptions()
    options.isHealthCard = false
    options.cardAttributes = attributes
    
    // For medical card set isHealthCard to true
    options.isHealthCard = false
   

   Note By default, the processing mode is set to the mode enabled in the subscription. However, if a user only requires data capture, then they can limit the processing mode by setting the following option:

     options.processingMode = ProcessingMode.DataCapture
   

2. Set the processing data:

    let idData = IdData ()
    idData.frontImage = capturedFrontImage
    idData.backImage = capturedBackImage
    idData.barcodeString = capturedBarcodeString
   

3. Process the ID:

    Controller.processId(imageData: idData, options: options, delegate: IDProcessingDelegate)
    
    // IDProcessingDelegate callback
    func imageProcessingFinished(result: ImageProcessingResult?) {
    	
    }
   

Processing a Facial Match

1. Set the facial data:

    	let facialMatchData = FacialMatchData()
   		facialMatchData.faceImageOne = downloadedImage
        facialMatchData.faceImageTwo = self.capturedLiveFace
   

2. Process the facial match:

    Controller.processFacialMatch(facialData: facialMatchData, delegate: FacialMatchDelegate)
    
    //FacialMatchDelegate callback
    func facialMatchFinished(result: FacialMatchResult?) {
    	if(result?.error == nil){
       	 //Success
    	}else{
        	// Error
    	}
    }
   

Frequently Asked Questions

While publishing the app in the Apple App store we are getting an "Unsupported Architecture" error?

All frameworks are “fat” (multi-architecture) binaries that contain slices for armv7, arm64, i386, and x86(64) CPU architectures. ARM slices are used by physical iOS devices, while i386 and x86(64) are used by the simulator.

Use the lipo command to check which slices are contained in the binaries:

	lipo -info <path to the file>

You can also use the lipo command to remove unwanted slices:

	lipo -remove i386 <Path to the file> -o <Output file path>

	lipo -remove x86_64 <Path to the file> -o <Output file path>