检测圈中的Android使用OpenCV的图像 [英] Detect Circle in image using OpenCV in Android
本文介绍了检测圈中的Android使用OpenCV的图像的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我开发一个 Android应用在我要检测从相机从画廊或捕获现有的图片浏览一圈。该浏览/拍摄的图像将显示到ImageView的。顺便说一句，我使用的的 OpenCVAndroid库的并妥善我编的。
I'm developing an android app in which I have to detect circle on existing image browse from gallery or capture from the camera. The browsed / captured image will be shown onto the ImageView. By the way, I'm using OpenCVAndroid Library and I compiled it properly.
我的Android应用任何帮助，我读了C，C ++或等检测圈，但我不明白'怎么为Android的不同语言。
Any help for my android app, I had read C, C++, or etc in detecting circles but I can't understand it 'coz its different languages for android.
感谢。
更新
好吧......这是我如何使用的。
Okay ... This is how I used.
if (requestCode == 1) { //Take Photo from Android Camera..
File f = new File(Environment.getExternalStorageDirectory().toString());
for (File temp : f.listFiles()) {
if (temp.getName().equals("temp.jpg")) {
f = temp;
break;
}
}
try {
Bitmap bitmap;
BitmapFactory.Options bitmapOptions = new BitmapFactory.Options();
bitmap = BitmapFactory.decodeFile(f.getAbsolutePath(),
bitmapOptions);
// bitmap = Bitmap.createScaledBitmap(bitmap, 70, 70, true);
String path = android.os.Environment
.getExternalStorageDirectory()
+ File.separator
+ "Phoenix" + File.separator + "default";
f.delete();
OutputStream outFile = null;
File file = new File(path, String.valueOf(System.currentTimeMillis()) + ".jpg");
try {
outFile = new FileOutputStream(file);
bitmap.compress(Bitmap.CompressFormat.JPEG, 85, outFile);
outFile.flush();
outFile.close();
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} catch (Exception e) {
e.printStackTrace();
}
/* convert bitmap to mat */
Mat mat = new Mat(bitmap.getWidth(), bitmap.getHeight(),
CvType.CV_8UC1);
Mat grayMat = new Mat(bitmap.getWidth(), bitmap.getHeight(),
CvType.CV_8UC1);
Utils.bitmapToMat(bitmap, mat);
/* convert to grayscale */
int colorChannels = (mat.channels() == 3) ? Imgproc.COLOR_BGR2GRAY
: ((mat.channels() == 4) ? Imgproc.COLOR_BGRA2GRAY : 1);
Imgproc.cvtColor(mat, grayMat, colorChannels);
/* reduce the noise so we avoid false circle detection */
Imgproc.GaussianBlur(grayMat, grayMat, new Size(9, 9), 2, 2);
// accumulator value
double dp = 1.2d;
// minimum distance between the center coordinates of detected circles in pixels
double minDist = 20;
// min and max radii (set these values as you desire)
int minRadius = 0, maxRadius = 0;
// param1 = gradient value used to handle edge detection
// param2 = Accumulator threshold value for the
// cv2.CV_HOUGH_GRADIENT method.
// The smaller the threshold is, the more circles will be
// detected (including false circles).
// The larger the threshold is, the more circles will
// potentially be returned.
double param1 = 70, param2 = 72;
/* create a Mat object to store the circles detected */
Mat circles = new Mat(bitmap.getWidth(),
bitmap.getHeight(), CvType.CV_8UC1);
/* find the circle in the image */
Imgproc.HoughCircles(grayMat, circles,
Imgproc.CV_HOUGH_GRADIENT, dp, minDist, param1,
param2, minRadius, maxRadius);
/* get the number of circles detected */
int numberOfCircles = (circles.rows() == 0) ? 0 : circles.cols();
/* draw the circles found on the image */
for (int i=0; i<numberOfCircles; i++) {
/* get the circle details, circleCoordinates[0, 1, 2] = (x,y,r)
* (x,y) are the coordinates of the circle's center*/
double[] circleCoordinates = circles.get(0, 0);
int x = (int) circleCoordinates[0], y = (int) circleCoordinates[1];
Point center = new Point(x, y);
int radius = (int) circleCoordinates[2];
/* circle's outline */
Core.circle(mat, center, radius, new Scalar(0,
255, 0), 4);
/* circle's center outline */
Core.rectangle(mat, new Point(x - 5, y - 5),
new Point(x + 5, y + 5),
new Scalar(0, 128, 255), -1);
}
/* convert back to bitmap */
Utils.matToBitmap(mat, bitmap);
viewImage.setImageBitmap(bitmap);
} catch (Exception e) {
e.printStackTrace();
}
}
我跑我的code以上，我的Android手机崩溃我拍照后，从相机的照片，我有这样的错误在logcat的应用程序：
I run my app with the code above,My Android phone is crashing after I take photo from camera and I have this errors in logcat:
02-10 06:54:15.773 8914-8914/com.example.cloud.circle E/AndroidRuntime﹕ FATAL EXCEPTION: main
java.lang.UnsatisfiedLinkError: n_Mat
at org.opencv.core.Mat.n_Mat(Native Method)
at org.opencv.core.Mat.<init>(Mat.java:477)
at com.example.cloud.circle.Image.onActivityResult(Image.java:152)
at android.app.Activity.dispatchActivityResult(Activity.java:3908)
at android.app.ActivityThread.deliverResults(ActivityThread.java:2532)
at android.app.ActivityThread.handleSendResult(ActivityThread.java:2578)
at android.app.ActivityThread.access$2000(ActivityThread.java:117)
at android.app.ActivityThread$H.handleMessage(ActivityThread.java:965)
at android.os.Handler.dispatchMessage(Handler.java:99)
at android.os.Looper.loop(Looper.java:130)
at android.app.ActivityThread.main(ActivityThread.java:3687)
at java.lang.reflect.Method.invokeNative(Native Method)
at java.lang.reflect.Method.invoke(Method.java:507)
at com.android.internal.os.ZygoteInit$MethodAndArgsCaller.run(ZygoteInit.java:867)
at com.android.internal.os.ZygoteInit.main(ZygoteInit.java:625)
at dalvik.system.NativeStart.main(Native Method)
请帮助我。谢谢你。
推荐答案
有关圆检测的详细解释可以发现的这里和的这里（虽然不是在Java中）。
A detailed explanation for circle detection can be found here and here (though not in Java).
我已经包括了一圈检测样品code段下面我从上面提供的2个链接囊括。在code被注释，所以它可以很容易理解。我假设位图图像位图已经有要分析的图像。
I have included a sample code snippet for circle detection below garnered from the 2 links I provided above. The code is commented, so it can be easily understood. I assume that the image bitmap bitmap already has the image you want to analyze.
/* convert bitmap to mat */
Mat mat = new Mat(bitmap.getWidth(), bitmap.getHeight(),
CvType.CV_8UC1);
Mat grayMat = new Mat(bitmap.getWidth(), bitmap.getHeight(),
CvType.CV_8UC1);
Utils.bitmapToMat(bitmap, mat);
/* convert to grayscale */
int colorChannels = (mat.channels() == 3) ? Imgproc.COLOR_BGR2GRAY
: ((mat.channels() == 4) ? Imgproc.COLOR_BGRA2GRAY : 1);
Imgproc.cvtColor(mat, grayMat, colorChannels);
/* reduce the noise so we avoid false circle detection */
Imgproc.GaussianBlur(grayMat, grayMat, new Size(9, 9), 2, 2);
// accumulator value
double dp = 1.2d;
// minimum distance between the center coordinates of detected circles in pixels
double minDist = 100;
// min and max radii (set these values as you desire)
int minRadius = 0, maxRadius = 0;
// param1 = gradient value used to handle edge detection
// param2 = Accumulator threshold value for the
// cv2.CV_HOUGH_GRADIENT method.
// The smaller the threshold is, the more circles will be
// detected (including false circles).
// The larger the threshold is, the more circles will
// potentially be returned.
double param1 = 70, param2 = 72;
/* create a Mat object to store the circles detected */
Mat circles = new Mat(bitmap.getWidth(),
bitmap.getHeight(), CvType.CV_8UC1);
/* find the circle in the image */
Imgproc.HoughCircles(grayMat, circles,
Imgproc.CV_HOUGH_GRADIENT, dp, minDist, param1,
param2, minRadius, maxRadius);
/* get the number of circles detected */
int numberOfCircles = (circles.rows() == 0) ? 0 : circles.cols();
/* draw the circles found on the image */
for (int i=0; i<numberOfCircles; i++) {
/* get the circle details, circleCoordinates[0, 1, 2] = (x,y,r)
* (x,y) are the coordinates of the circle's center
*/
double[] circleCoordinates = circles.get(0, i);
int x = (int) circleCoordinates[0], y = (int) circleCoordinates[1];
Point center = new Point(x, y);
int radius = (int) circleCoordinates[2];
/* circle's outline */
Core.circle(mat, center, radius, new Scalar(0,
255, 0), 4);
/* circle's center outline */
Core.rectangle(mat, new Point(x - 5, y - 5),
new Point(x + 5, y + 5),
new Scalar(0, 128, 255), -1);
}
/* convert back to bitmap */
Utils.matToBitmap(mat, bitmap);
更新
在为prevent的的UnsatisfiedLinkError ，使用OpenCV库的功能之前，请确保您加载的库文件，我在下面做的：
In order to prevent the UnsatisfiedLinkError, before using OpenCV library's functions, ensure you load the library files, as I have done below:
if (!OpenCVLoader.initDebug()) {
Log.e(TAG, "Cannot connect to OpenCV Manager");
}
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