目前Android平台上进行人脸特征识别非常火爆，本人研究生期间一直从事人脸特征的处理，所以曾经用过一段ASM（主动形状模型）提取人脸基础特征点，所以这里采用JNI的方式将ASM在Android平台上进行了实现，同时在本应用实例中，给出了几个其他的图像处理的示例。
由于ASM (主动形状模型，Active Shape Model)的核心算法比较复杂，所以这里不进行算法介绍，我之前写过一篇详细的算法介绍和公式推导，有兴趣的朋友可以参考下面的连接： ASM（主动形状模型）算法详解
接下来介绍本应用的实现。 首先，给出本应用的项目源码： Android ASM Demo 在这个项目源码的README中详细介绍了怎么配置运行时环境，请仔细阅读。 本项目即用到了Android JNI开发，又用到了Opencv4Android，所以，配置起来还是很复杂的。Android JNI开发配置请参考：Android JNI，Android 上使用Opencv请参考:Android Opencv
整个应用的代码比较多，所以如果想很好的了解项目原理，最好还是将代码下载下来仔细看看。
首先给出本地cpp代码，下面的本地cpp代码负责调用stasm提供的c语言接口：
cv;;CascadeClassifier cascade;bool init = false;const String APP_DIR = “/data/data/com.example.asm/app_data/”;extern “C” {/* * do Canny edge detect */JNIEXPORT void JNICALL Java_com_example_asm_NativeCode_DoCanny(JNIEnv* env,jobject obj, jlong matSrc, jlong matDst, jdouble threshold1 = 50,jdouble threshold2 = 150, jint aperatureSize = 3) {Mat * img = (Mat *) matSrc;Mat * dst = (Mat *) matDst;cvtColor(*img, *dst, COLOR_BGR2GRAY);Canny(*img, *dst, threshold1, threshold2, aperatureSize);}/* * face detection * matDst: face region * scaleFactor = 1.1 * minNeighbors = 2 * minSize = 30 * 30 */JNIEXPORT void JNICALL Java_com_example_asm_NativeCode_FaceDetect(JNIEnv* env,jobject obj, jlong matSrc, jlong matDst, jdouble scaleFactor, jint minNeighbors, jint minSize) {Mat * src = (Mat *) matSrc;Mat * dst = (Mat *) matDst;float factor = 0.3;Mat img;resize(*src, img, Size((*src).cols * factor, (*src).rows * factor));String cascadeFile = APP_DIR + “haarcascade_frontalface_alt2.xml”;if (!init) {cascade.load(cascadeFile);init = true;}if (cascade.empty() != true) {vector<Rect> faces;cascade.detectMultiScale(img, faces, scaleFactor, minNeighbors, 0| CV_HAAR_FIND_BIGGEST_OBJECT| CV_HAAR_DO_ROUGH_SEARCH| CV_HAAR_SCALE_IMAGE, Size(minSize, minSize));for (int i = 0; i < faces.size(); i++) {Rect rect = faces[i];rect.x /= factor;rect.y /= factor;rect.width /= factor;rect.height /= factor;if (i == 0) {(*src)(rect).copyTo(*dst);}rectangle(*src, rect.tl(), rect.br(), Scalar(0, 255, 0, 255), 3);}}}/* * do ASM * error code: * -1: illegal input Mat * -2: ASM initialize error * -3: no face detected */JNIEXPORT jintArray JNICALL Java_com_example_asm_NativeCode_FindFaceLandmarks(JNIEnv* env, jobject, jlong matAddr, jfloat ratioW, jfloat ratioH) {const char * PATH = APP_DIR.c_str();clock_t StartTime = clock();jintArray arr = env->NewIntArray(2 * stasm_NLANDMARKS);jint *out = env->GetIntArrayElements(arr, 0);Mat img = *(Mat *) matAddr;cvtColor(img, img, COLOR_BGR2GRAY);if (!img.data) {out[0] = -1; // error code: -1(illegal input Mat)out[1] = -1;img.release();env->ReleaseIntArrayElements(arr, out, 0);return arr;}int foundface;*) img.data,img.cols, img.rows, ” “, PATH)) {out[0] = -2; // error code: -2(ASM initialize failed)out[1] = -2;img.release();env->ReleaseIntArrayElements(arr, out, 0);return arr;}if (!foundface) {out[0] = -3; // error code: -3(no face found)out[1] = -3;img.release();env->ReleaseIntArrayElements(arr, out, 0);return arr;} else {for (int i = 0; i < stasm_NLANDMARKS; i++) {out[2 * i] = cvRound(landmarks[2 * i] * ratioW);out[2 * i + 1] = cvRound(landmarks[2 * i + 1] * ratioH);}}double TotalAsmTime = double(clock() – StartTime) / CLOCKS_PER_SEC;__android_log_print(ANDROID_LOG_INFO, “com.example.asm.native”,”running in native code, \nStasm Ver:%s Img:%dx%d —> Time:%.3f secs.”, stasm_VERSION,img.cols, img.rows, TotalAsmTime);img.release();env->ReleaseIntArrayElements(arr, out, 0);return arr;}}
stasm代码比较多，这里不具体给出，这里特别给出一下Android.mk这个Android平台JNI代码的makefile
LOCAL_PATH := $(call my-dir))OPENCV_CAMERA_MODULES:=offOPENCV_INSTALL_MODULES:=onOPENCV_LIB_TYPE:=STATICifeq (“$(wildcard $(OPENCV_MK_PATH))”,””)#try to load OpenCV.mk from default install locationinclude /home/wesong/software/OpenCV-2.4.10-android-sdk/sdk/native/jni/OpenCV.mk)endif= $(wildcard $(LOCAL_PATH)/stasm/*.cpp) \ $(wildcard $(LOCAL_PATH)/stasm/MOD_1/*.cpp)LOCAL_SRC_FILES := Native.cpp \)/%=%)LOCAL_LDLIBS += -llog -ldl))LOCAL_MODULE := opencv_java-prebuildLOCAL_SRC_FILES := libopencv_java.so)却坐在不足一平米的椅子上。
