Acuant iOS SDK v11.3.2

2020年3月

查看https://github.com/Acuant/iOSSDKV11/releases以获取发行说明。

简介

本文件提供了关于 Acuant iOS SDK 的详细信息。下面描述了 Acuant 推荐的工作流程。

注意可接受的图像应裁剪良好、清晰且无反光，分辨率至少为 300 dpi（用于数据采集）或 600 dpi（用于验证）。宽高比应合理并与身份证相匹配。

先决条件

iOS 版本 11.0 或更高

模块

SDK 包含以下模块

Acuant Face Capture Library (AcuantFaceCapture)

使用原生 iOS 摄像头捕获人脸。

Acuant Passive Liveness Library (AcuantPassiveLiveness)

使用专用算法检测真人

Acuant Common Library (AcuantCommon)

包含所有共享内部模型和支持类

Acuant Camera Library (AcuantCamera)

使用 iOS 原生摄像头库实现
使用 AcuantImagePreparation 进行裁剪

Acuant Image Preparation Library (AcuantImagePreparation)

包含所有图像处理，如裁剪、计算锐度和反光

Acuant Document Processing Library (AcuantDocumentProcessing)

包含所有上传文档图像、处理和获取结果的方法

Acuant人脸匹配库（AcuantFaceMatch）

包含一种用于匹配两张人脸图像的方法

Acuant HG 生存性库（AcuantHGLiveness）

使用iOS本地摄像头库以专有算法捕获面部生存性

Acuant IP 生存性库（AcuantIPLiveness）

使用专用算法检测真人

手动设置

添加以下依赖的嵌入框架

AcuantFaceCapture
AcuantPassiveLiveness
AcuantCommon
AcuantImagePreparation
AcuanCamera
AcuantDocumentProcessing
AcuantHGLiveness
AcuantFaceMatch
AcuantIPLiveness - iProov.framework - KeychainAccess.framework - SocketIO.framework - Starscream.framework - SwiftyJSON.framework

在Xcode中打开您的项目，导航到应用程序项目设置中的“构建阶段”标签。添加一个新的“运行脚本”。

将以下内容添加到脚本中。

/usr/local/bin/carthage copy-frameworks

创建新的 inputFileList.xcfilelist 和 outputFileList.xcfilelist。将必要的框架添加到这两个文件中。请参阅存储库中的示例。
将.xcfilelist 添加到您的运行脚本中。获取更多信息，请访问 https://github.com/Carthage/Carthage。

使用COCOAPODS

如果您正在使用COCOAPODS，则添加以下Podfile

 platform :ios, '11.0'
 pod 'AcuantiOSSDKV11', '~> 11.3.2'

在构建设置中为所有Acuant pod框架启用“BUILD_FOR_DISTRIBUTION”。

使用Cocoapods。将其添加到Podfile中。

  post_install do |installer|
  	installer.pods_project.targets.each do |target|
  		if ['AcuantiOSSDKV11', 'KeychainAccess', 'Socket.IO-Client-Swift', 'Starscream' 'SwiftyJSON'].include? target.name
  			target.build_configurations.each do |config|
  				config.build_settings['BUILD_LIBRARY_FOR_DISTRIBUTION'] = 'YES'
  			end
  		end
  	end
  end

手动

必需设置

创建一个名为 AcuantConfig 的 plist 文件，其中包含以下详细信息

 <?xml version="1.0" encoding="UTF-8"?>
 <!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
 <plist version="1.0">
 	<dict>
 		<key>acuant_username</key>
 		<string>[email protected]</string>
 		<key>acuant_password</key>
 		<string>xxxxxxxxxx</string>
 		<key>acuant_subscription</key>
 		<string>xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx</string>
 		<key>frm_endpoint</key>
 		<string>https://frm.acuant.net</string>
 		<key>passive_liveness_endpoint</key>
 		<string>https://passlive.acuant.net</string>
 		<key>med_endpoint</key>
 		<string>https://medicscan.acuant.net</string>
 		<key>assureid_endpoint</key>
 		<string>https://services.assureid.net</string>
 	</dict>
 </plist>

使用AcuantCamera捕获图像

AcuantCamera最好在纵向模式下使用。在使用摄像头之前锁定应用的方向。

设置回调

 // Returns the image and barcodeString captured from device
 public protocol CameraCaptureDelegate {
 	func setCapturedImage(image:Image, barcodeString:String?)
 }

打开摄像头

注意：现在选项通过一个选项对象定义。请参阅 AcuantCameraOptions 获取所有可配置的字段。

 let options = AcuantCameraOptions(autoCapture: true, hideNavigationBar: true)
 let documentCameraController = DocumentCameraController.getCameraController(delegate:self!, cameraOptions: options)
 
 navigationController.pushViewController(documentCameraController, animated: false)

获取捕获的图像

 public protocol CameraCaptureDelegate {
 	func setCapturedImage(image:Image, barcodeString:String?)
 }

使用DocumentCaptureSesssion（查看DocumentCameraController.swift以获取参考）进行自定义UI

获取DocumentCaptureSesssion。

 @objc public protocol DocumentCaptureDelegate {
     func readyToCapture() // gets called when triggering capture
     func documentCaptured(image:UIImage, barcodeString:String?) // gets called with captured result
 }
 
 let captureSession = DocumentCaptureSession.getDocumentCaptureSession(
 	delegate: DocumentCaptureDelegate, // session callback
 	frameDelegate: FrameAnalysisDelegate, // frame anaylsis callback
 	autoCapture:Bool, // enable frame analysis
 	captureDevice:AVCaptureDevice?) // AV Capture Device

开始会话，然后将会话添加到AVCaptureVideoPreviewLayer。

 captureSession.start() // will start the capture session.
 let videoPreviewLayer = AVCaptureVideoPreviewLayer(session: captureSession)
 //add custom ui

接收帧结果。

 @objc public enum FrameResult : Int{
     case NO_DOCUMENT, // No document
     	SMALL_DOCUMENT, // Document is small
     	BAD_ASPECT_RATIO, // Document type does not match aspect ratio
     	GOOD_DOCUMENT, // Document is good to trigger capture
     	DOCUMENT_NOT_IN_FRAME // Document is not in frame
 }
 
 @objc public protocol FrameAnalysisDelegate{
     func onFrameAvailable(frameResult: FrameResult, points: Array<CGPoint>?)
 }

触发捕获。
```
 captureSession.enableCapture()
```
DocumentCaptureDelegate将执行并带有结果
```
 func documentCaptured(image:UIImage, barcodeString:String?)
```
注意： AcuantCamera依赖于<ссxsstrong>AcuantImagePreparation和< Получитеstrong>AcuantCommon。

AcuantImagePreparation

此模块包含所有图像准备功能。

初始化

AcuantImagePreparation.initialize(delegate: InitializationDelegate)

public protocol InitializationDelegate {
	func initializationFinished(error: AcuantError?);
}

注意：如果您在初始化时没有使用配置文件，那么请使用以下语句（提供适当的凭据以供用户名、密码和订阅ID使用）

Credential.setUsername(username: "xxx")
Credential.setPassword(password: "xxxx")
Credential.setSubscription(subscription: "xxxxxx")

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

Credential.setEndpoints(endpoints: endpoints)

AcuantImagePreparation.initialize(delegate:self)

不带订阅ID的初始化

AcuantImagePreparation可以通过提供用户名和密码来初始化。但是，如果不提供订阅ID，则应用程序只能捕获图像并获取图像。没有订阅ID

只能使用<олучитеstrong>AcuantCamera、AcuantImagePreparation和<учитеstrong>AcuantHGLiveness模块。
SDK可用于捕获身份证明文件。

捕获的图像可以从SDK中导出。请参阅AcuantCamera项目中的DocumentCaptureDelegate协议。

public protocol DocumentCaptureDelegate {
	func readyToCapture()
	func documentCaptured(image:UIImage, barcodeString:String?)
}

裁剪

在捕获图像后，将其发送到裁剪库进行裁剪。

	public class func crop(data: CroppingData)->Image

	// CroppingData & Image are part of AcuantCommon
	// Sample

	let croppingData  = CroppingData()
    croppingData.image = image // UIImage

    let croppedImage = AcuantImagePreparation.crop(data: croppingData)

清晰度

sharpness方法返回 image 的清晰度值。如果清晰度值大于50，则认为图像是清晰的（不是模糊的）。

	public class func sharpness(image: UIImage)->Int

反射光

《glare` 方法返回图像的光线反射值。如果光线反射值为100，则图像不包含光线反射。如果光线反射值为0，则图像包含光线反射。

	public class func glare(image: UIImage)->Int

AcuantDocumentProcessing

在捕获文档图像后，可以使用以下步骤进行处理。

注意：如果上传失败并出现错误，请使用更好的图像重试图像上传。

创建实例

 public class func createInstance(options:IdOptions,delegate:CreateInstanceDelegate)

 public protocol CreateInstanceDelegate{
 	func instanceCreated(instanceId : String?,error:AcuantError?);
 }

上传图像

 public class func uploadImage(instancdId:String,data:IdData,options:IdOptions,delegate:UploadImageDelegate)

 public protocol UploadImageDelegate{
 	func imageUploaded(error: AcuantError?,classification:Classification?);
 }

获取数据

 public class func getData(instanceId:String,isHealthCard:Bool,delegate:GetDataDelegate?)

 public protocol UploadImageDelegate{
 	func imageUploaded(error: AcuantError?,classification:Classification?);
 }

删除实例

 public class func deleteInstance(instanceId : String,type:DeleteType, delegate:DeleteDelegate)

 public protocol DeleteDelegate {
 	func instanceDeleted(success : Bool)
 }

Acuant Face Capture

（可选）设置默认图像。在示例应用程序项目的“Assets”目录中定位“acuant_default_face_image.png”。如果需要，将其添加到您的应用程序中。

在应用程序的可本地化字符串中设置本地化字符串

 "acuant_face_camera_initial" = "Align face to start capture";
 "acuant_face_camera_face_too_close" = "Too Close! Move Away";
 "acuant_face_camera_face_too_far" = "Move Closer";
 "acuant_face_camera_face_has_angle" =  "Face has Angle. Do not tilt";
 "acuant_face_camera_face_not_in_frame" =  "Move in Frame";
 "acuant_face_camera_face_moved" = "Hold Steady";
 "acuant_face_camera_capturing_2" = "Capturing\n2...";
 "acuant_face_camera_capturing_1" = "Capturing\n1...";

设置任何必要的UI自定义

 class FaceAcuantCameraOptions{
 	public let totalCaptureTime: Int //totoal time to capture
 	public let bracketColorDefault: CGColor //bracket color default (no face)
 	public let bracketColorError: CGColor //bracket color error (error in face requirements)
 	public let bracketColorGood: CGColor //bracket color good (good face requirements)
 	public let fontColorDefault: CGColor //font color default
 	public let fontColorError: CGColor //font color error
 	public let fontColorGood: CGColor //font color good
 	public let defaultImageUrl: String //default image
 	public let showOval: Bool // show oval
 }
 
 //example
 let options = FaceAcuantCameraOptions()

获取控制器并将其推送到navigationController

 let controller = AcuantFaceCaptureController()
 	controller.options = options
 	controller.callback = { [weak self]
 		(image: UIImage?) in
 			
 			if(image == nil){
 				//user canceled
 			}
         
 	}
 		
 self.navigationController.pushViewController(controller, animated: true)

使用捕获结果使用回调。

Acuant Passive Liveness

Acuant建议使用`LiveAssessment`属性而不是分数来评估响应。《AcuantPassiveLiveness.startSelfieCapture`会返回一个重缩放的图像。

遵循以下建议，以有效地处理图像以实现被动活体识别。

图像要求

高度：最小480像素，建议720或1080像素
压缩：不建议对图像进行压缩（JPEG 70级别或以上是可以接受的）。为了获得最佳效果，请使用未压缩的图像。

人脸要求

垂直旋转：面俯仰角和偏航角：从-20到20度，±3度
平面旋转：面翻滚角：从-30到30度，±3度
瞳距：眼睛之间的最小距离 90 ± 5像素
面部大小：至少200像素的任何一个维度
每张图像中的面部：1
太阳镜：必须摘除

捕获要求

以下可能显着增加错误或错误结果

使用运动模糊效果
纹理过滤
面部及其最近周围环境的聚光灯
光线条件差或彩色光的环境

注意此API不支持使用鱼眼镜头。

使用UIImage获取被动活度结果

 //liveness request
 class AcuantLivenessRequest{
     public let image: UIImage
     public init(image: UIImage)
 }
 
 //liveness response
 class AcuantLivenessResponse{
 	public let score: Int
 	public let result: AcuantLivenessAssessment
 	
 	public enum AcuantLivenessAssessment: String{
 		case Error
 		case PoorQuality
 		case Live
 		case NotLive
 	}
 }
 
 //liveness response
 class AcuantLivenessError{
 	public let errorCode: AcuantLivenessErrorCode?
 	public let description: String?
 	
 	
 	public enum AcuantLivenessErrorCode: String{
 	    case Unknown
 	    case FaceTooClose
 	    case FaceNotFound
 	    case FaceTooSmall
 	    case FaceAngleTooLarge
 	    case FailedToReadImage
 	    case InvalidRequest
 	    case InvalidRequestSettings
 	    case Unauthorized
 	    case NotFound
 	    case InternalError
 	    case InvalidJson
 	}
 }
 
 //example
 AcuantPassiveLiveness.postLiveness(request: AcuantLivenessRequest(image: image)){ [weak self]
 	(result: AcuantLivenessResponse?, error: AcuantLivenessError?) in
 		//response
 }

AcuantHGLiveness

该模块通过使用眨眼检测来检查是否存在活动（主题是否为活人）。该用户界面代码包含在示例应用（FaceLivenessCameraController.swift）中，客户可以根据具体需求对其进行修改。

Sample应用中的Acuant UI

// Code for HG Live controller
let liveFaceViewController = FaceLivenessCameraController()
liveFaceViewController.delegate : AcuantHGLiveFaceCaptureDelegate = self
self.navigationController.pushViewController(liveFaceViewController, animated: true)

自定义UI，创建面部活度捕捉会话

enum AcuantFaceType : Int {

    case NONE // No face
	
    case FACE_TOO_CLOSE // face is too close camera
	
    case FACE_MOVED // face moved from its original position
	
    case FACE_TOO_FAR // face is too far from camera
		
    case FACE_NOT_IN_FRAME // face is not in frame
    
    case FACE_GOOD_DISTANCE // face is good distance and in frame
}

public protocol AcuantHGLiveFaceCaptureDelegate {
		func liveFaceDetailsCaptured(liveFaceDetails: LiveFaceDetails?, faceType: AcuantHGLiveness.AcuantFaceType)
}

public class func getFaceCaptureSession(delegate:AcuantHGLiveFaceCaptureDelegate?, captureDevice: AVCaptureDevice?)-> FaceCaptureSession


let faceCaptureSession = AcuantHGLiveness.getFaceCaptureSession(delegate: self, captureDevice: captureDevice)

AcuantIPLiveness

AcuantIPLiveness模块用于检查主题是否为活人。

运行设置

 AcuantIPLiveness.performLivenessSetup(delegate:LivenessSetupDelegate)

 public protocol LivenessSetupDelegate{
 	func livenessSetupSucceeded(result:LivenessSetupResult) // Called when setup succeeds
 	func livenessSetupFailed(error:AcuantError) // Called when setup failed
 }

 public class LivenessSetupResult {
 	public var apiKey : String
 	public var token : String
 	public var userId : String
 	public var apiEndpoint : String

 }

进行活度测试

注意您可以使用 LivenessSetupResult 根据需要自定义界面。

 // Adjust various colors for the camera preview:
 setupResult.ui.lineColor = .white
 setupResult.ui.backgroundColor = .black
 setupResult.ui.loadingTintColor = .lightGray
 setupResult.ui.notReadyTintColor = .orange
 setupResult.ui.readyTintColor = .green

 setupResult.ui.title = "title" // Specify a custom title to be shown. Defaults to nil which will show an auto generated message. Set to empty string ("") to hide the message entirely.
 setupResult.ui.regularFont = "SomeFont"
 setupResult.ui.boldFont = "SomeFont-Bold"
 setupResult.ui.fonts = ["SomeFont", "SomeFont-Bold"] // If using custom fonts, specify them here (don't forget to add them to your Info.plist!)
 setupResult.ui.logoImage = UIImage(named: "foo")
 setupResult.ui.scanLineDisabled = false // Disables the vertical sweeping scanline while flashing
 setupResult.ui.autoStartDisabled = false // Disable the "auto start" countdown functionality. The user will have to tap the screen to start liveness test

 AcuantIPLiveness.performLivenessTest(setupResult:LivenessSetupResult, delegate:LivenessTestDelegate)
 
 public protocol LivenessTestDelegate{
 	func livenessTestCompleted() // This is for the test; called when Enroll is complete
 	func livenessTestCompletedWithError(error:AcuantError?) // This is for the test; called when Enroll is complete and error occured
 	func livenessTestProcessing(progress: Double, message: String) // This is for real-time notifications of progress of liveness test. It will be called after user captures live face. It is intended to be used for custom UI progress notification.

 }

获取活度测试结果

 AcuantIPLiveness.getLivenessTestResult(token:String,userId:String,delegate:LivenessTestResultDelegate)
 
 public protocol LivenessTestResultDelegate{
 	func livenessTestResultReceived(result:LivenessResult) // Called when test result was received successfully
 	func livenessTestResultReceiveFailed(error:AcuantError) // Called when test result was not received
 }

 public class LivenessTestResult {
 	public var passedLivenessTest : Bool = false
 	public var image : UIImage? = nil
 
 }

以下是依赖列表

iProov.framework
KeychainAccess.framework
SocketIO.framework
Startscream.framework
SwiftyJSON.framework

AcuantFaceMatch

此模块用于匹配两张面部图像

	public class func processFacialMatch(facialData : FacialMatchData, delegate : FacialMatchDelegate)

	public protocol FacialMatchDelegate {
		func facialMatchFinished(result:FacialMatchResult?)
	}

	public class FacialMatchData{
		public var faceImageOne : UIImage // Facial image from ID Card (image gets compressed by 80%)
		public var faceImageTwo : UIImage // Facial image from selfie capture during liveness check (image gets compressed by 80%)
	}

错误代码

public class AcuantErrorCodes{
	public static let ERROR_InvalidCredentials = -1
	public static let ERROR_InvalidLicenseKey = -2
	public static let ERROR_InvalidEndpoint = -3
	public static let ERROR_InitializationNotFinished = -4
	public static let ERROR_Network = -5
	public static let ERROR_InvalidJson = -6
	public static let ERROR_CouldNotCrop = -7
	public static let ERROR_NotEnoughMemory = -8
	public static let ERROR_BarcodeCaptureFailed = -9
	public static let ERROR_BarcodeCaptureTimedOut = -10
	public static let ERROR_BarcodeCaptureNotAuthorized = -11
	public static let ERROR_LiveFaceCaptureNotAuthorized = -12
	public static let ERROR_CouldNotCreateConnectInstance = -13
	public static let ERROR_CouldNotUploadConnectImage = -14
	public static let ERROR_CouldNotUploadConnectBarcode = -15
	public static let ERROR_CouldNotGetConnectData = -16
	public static let ERROR_CouldNotProcessFacialMatch = -17
	public static let ERROR_CardWidthNotSet = -18
	public static let ERROR_CouldNotGetHealthCardData = -19
	public static let ERROR_CouldNotClassifyDocument = -20
	public static let ERROR_LowResolutionImage = -21
	public static let ERROR_BlurryImage = -22
	public static let ERROR_ImageWithGlare = -23
	public static let ERROR_CouldNotGetIPLivenessToken = -24
	public static let ERROR_NotALiveFace = -25
	public static let ERROR_CouldNotAccessLivenessData = -26
}

错误描述

public class AcuantErrorDescriptions {
	public static let ERROR_DESC_InvalidCredentials = "Invalid credentials"
	public static let ERROR_DESC_InvalidLicenseKey = "Invalid License Key"
	public static let ERROR_DESC_InvalidEndpoint = "Invalid endpoint"
	public static let ERROR_DESC_Network = "Network problem"
	public static let ERROR_DESC_InitializationNotFinished = "Initialization not finished"
	public static let ERROR_DESC_InvalidJson = "Invalid Json response"
	public static let ERROR_DESC_CouldNotCrop = "Could not crop image"
	public static let ERROR_DESC_BarcodeCaptureFailed = "Barcode capture failed"
	public static let ERROR_DESC_BarcodeCaptureTimedOut = "Barcode capture timed out"
	public static let ERROR_DESC_BarcodeCaptureNotAuthorized = "Barcode capture is not authorized"
	public static let ERROR_DESC_LiveFaceCaptureNotAuthorized = "Live face capture is not authorized"
	public static let ERROR_DESC_CouldNotCreateConnectInstance = "Could not create connect Instance"
	public static let ERROR_DESC_CouldNotUploadConnectImage = "Could not upload image to connect instance"
	public static let ERROR_DESC_CouldNotUploadConnectBarcode = "Could not upload barcode to connect instance"
	public static let ERROR_DESC_CouldNotGetConnectData = "Could not get connect image data"
	public static let ERROR_DESC_CardWidthNotSet = "Card width not set"
	public static let ERROR_DESC_CouldNotGetHealthCardData = "Could not get health card data"
	public static let ERROR_DESC_CouldNotClassifyDocument = "Could not classify document"
	public static let ERROR_DESC_LowResolutionImage = "Low resolution image"
	public static let ERROR_DESC_BlurryImage = "Blurry image"
	public static let ERROR_DESC_ImageWithGlare = "Image has glare"
	public static let ERROR_DESC_CouldNotGetIPLivenessToken = "Could not get face liveness token"
	public static let ERROR_DESC_NotALiveFace = "Not a live face"
	public static let ERROR_DESC_CouldNotAccessLivenessData = "Could not access liveness data"
}

图片

public class Image {
	public var image: UIImage? = nil
	public var dpi: Int = 0 // dpi value of the captured image
	public var error: AcuantError? = nil
	public var isCorrectAspectRatio = false // If the captured image has the correct aspect ratio
	public var aspectRatio: Float = 0.0 // Aspect ratio of the captured image
	public var points: Array<CGPoint> = []
	public var isPassport = false
	public init(){}
}

AcuantCameraOptions

public class AcuantCameraOptions {
    timeInMsPerDigit: Int = 900,
    digitsToShow: Int = 2,
    allowBox: Bool = true,
    autoCapture: Bool = true,
    hideNavigationBar: Bool = true,
    bracketLengthInHorizontal: Int = 80,
    bracketLengthInVertical: Int = 50,
    defaultBracketMarginWidth: CGFloat = 0.5,
    defaultBracketMarginHeight: CGFloat = 0.6,
    colorHold: CGColor = UIColor.yellow.cgColor,
    colorCapturing: CGColor = UIColor.green.cgColor,
    colorBracketAlign: CGColor = UIColor.black.cgColor,
    colorBracketCloser: CGColor = UIColor.red.cgColor,
    colorBracketHold: CGColor = UIColor.yellow.cgColor,
    colorBracketCapture: CGColor = UIColor.green.cgColor
}

IdOptions

public class IdOptions {
    public var cardSide: CardSide = CardSide.Front
    public var isHealthCard: Bool = false
    public var isRetrying: Bool = false
    public var authenticationSensitivity: AuthenticationSensitivity = AuthenticationSensitivity.Normal
}

常见问题

为什么在Apple App Store发布应用时会出现“不支持架构”错误？

所有框架都是 fat（多架构）二进制文件，包含切片，用于 armv7、arm64、 i386 和 x86(64) CPU 架构。ARM 切片由物理 iOS 设备使用，而 i386 和 x86(64) 用于模拟器。

使用 lipo 命令来检查二进制中包含哪些切片

	lipo -info <path to the file>

您也可以使用 lipo 命令来删除不需要的切片

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

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

为什么在存档样本应用程序时出现代码签名“AcuantCommon.framework”错误？

Acuant 为所有模拟器和设备所需的 CPU 架构提供支持。然而，在导出或发布到 Test Flight/App Store 时，应从框架二进制文件中删除模拟器架构（i386 和 x86(64)）。

存档应用程序。
选择存档，然后点击 分发应用> App Store> 导出。

我该如何混淆我的 iOS 应用程序？

Acuant 不提供混淆工具，但是有一些第三方工具可供选择，包括 iXGuard 和 Arxan。

本文档包含由 Acuant 和其各自许可方拥有的专有和保密信息及创意作品。未经 Acuant 事先书面明确许可，禁止以任何形式或任何手段全部或部分使用、复制、发布、分发、展示、修改或传输此类技术。除非 Acuant 以书面形式明确提供，否则拥有此信息不视为授予任何 Acuant 知识产权的许可或权利，无论是由于先占、暗示还是其他方式。

AssureID 和 i-Dentify 是 Acuant Inc. 的商标。本文档中提到的其他 Acuant 产品或服务名称或标志是 Acuant 的商标或注册商标。

所有 3M 商标是 Gemalto Inc. 的商标。

Windows 是微软公司的注册商标。

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AcuantTest 0.0.1-b

AcuantTest 0.0.1-b

AcuantTest 0.0.1-b

Acuant iOS SDK v11.3.2

简介

先决条件

模块

手动设置

使用COCOAPODS

必需设置

使用AcuantCamera捕获图像

AcuantImagePreparation

不带订阅ID的初始化

裁剪

清晰度

反射光

AcuantDocumentProcessing

Acuant Face Capture

Acuant Passive Liveness

图像要求

人脸要求

捕获要求

AcuantHGLiveness

AcuantIPLiveness

AcuantFaceMatch

错误代码

错误描述

图片

AcuantCameraOptions

IdOptions

常见问题

为什么在Apple App Store发布应用时会出现“不支持架构”错误？

为什么在存档样本应用程序时出现代码签名“AcuantCommon.framework”错误？

我该如何混淆我的 iOS 应用程序？