Android平台生成二维码并实现扫描 & 识别功能
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1.二维码的前世今生
“二维条码/二维码(2-dimensional bar code)是用某种特定的几何图形按一定规律在平面(二维方向上)分布的黑白相间的图形记录数据符号信息的;在代码编制上巧妙地利用构成计算机内部逻辑基础的“0”、“1”比特流的概念,使用若干个与二进制相对应的几何形体来表示文字数值信息,通过图象输入设备或光电扫描设备自动识读以实现信息自动处理:它具有条码技术的一些共性:每种码制有其特定的字符集;每个字符占有一定的宽度;具有一定的校验功能等。同时还具有对不同行的信息自动识别功能、及处理图形旋转变化点。 [1] ”
上面是百度百科的解释。既然有二维码,那么肯定有一维码。
一维码。最为常见的就是食品 & 书本后面的条码。
条码起源与20世纪40年代,后来在1970年 UPC码发明,并开始广泛应用与食品包装。
具体的介绍可以看百度百科 一维码。
其实二维码与一维码本质上是类似的,就跟一维数组和二维数组一样。
2.二维码的java支持库
为了让java或者说android方便继承条码的功能,google就开发了一个zxing的库:
https://github.com/zxing/zxing
3.生成二维码
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | public class EncodeThread { public static void encode( final String url, final int width, final int height, final EncodeResult result) { if (result == null ) { return ; } if (TextUtils.isEmpty(url)) { result.onEncodeResult( null ); return ; } new Thread() { @Override public void run() { try { MultiFormatWriter writer = new MultiFormatWriter(); Hashtable<EncodeHintType, String> hints = new Hashtable<>(); hints.put(EncodeHintType.CHARACTER_SET, "utf-8" ); BitMatrix bitMatrix = writer.encode(url, BarcodeFormat.QR_CODE, width, height, hints); Bitmap bitmap = parseBitMatrix(bitMatrix); result.onEncodeResult(bitmap); return ; } catch (WriterException e) { e.printStackTrace(); } result.onEncodeResult( null ); } }.start(); } /** * 生成二维码内容<br> * * @param matrix * @return */ public static Bitmap parseBitMatrix(BitMatrix matrix) { final int QR_WIDTH = matrix.getWidth(); final int QR_HEIGHT = matrix.getHeight(); int [] pixels = new int [QR_WIDTH * QR_HEIGHT]; //this we using qrcode algorithm for ( int y = 0 ; y < QR_HEIGHT; y++) { for ( int x = 0 ; x < QR_WIDTH; x++) { if (matrix.get(x, y)) { pixels[y * QR_WIDTH + x] = 0xff000000 ; } else { pixels[y * QR_WIDTH + x] = 0xffffffff ; } } } Bitmap bitmap = Bitmap.createBitmap(QR_WIDTH, QR_HEIGHT, Bitmap.Config.ARGB_8888); bitmap.setPixels(pixels, 0 , QR_WIDTH, 0 , 0 , QR_WIDTH, QR_HEIGHT); return bitmap; } public interface EncodeResult { void onEncodeResult(Bitmap bitmap); } } |
zxing 支持很多条码格式:我们这里使用QR_CODE码。也就是我们常见的微信里面的二维码。
我们先来分析下这段代码:
MultiFormatWriter writer = new MultiFormatWriter();
这个是一个工具类,把所有支持的几个write写在里面了。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | public BitMatrix encode(String contents, BarcodeFormat format, int width, int height, Map<EncodeHintType,?> hints) throws WriterException { Writer writer; switch (format) { case EAN_8: writer = new EAN8Writer(); break ; case UPC_E: writer = new UPCEWriter(); break ; case EAN_13: writer = new EAN13Writer(); break ; case UPC_A: writer = new UPCAWriter(); break ; case QR_CODE: writer = new QRCodeWriter(); break ; case CODE_39: writer = new Code39Writer(); break ; case CODE_93: writer = new Code93Writer(); break ; case CODE_128: writer = new Code128Writer(); break ; case ITF: writer = new ITFWriter(); break ; case PDF_417: writer = new PDF417Writer(); break ; case CODABAR: writer = new CodaBarWriter(); break ; case DATA_MATRIX: writer = new DataMatrixWriter(); break ; case AZTEC: writer = new AztecWriter(); break ; default : throw new IllegalArgumentException( "No encoder available for format " + format); } return writer.encode(contents, format, width, height, hints); } |
这是官方最新支持的格式,具体看引入的jar里面支持的格式。
对与bitmatrix的结果,通过摸个算法,设置每个点白色,或者黑色。
最后创建一张二维码的图片。
4.识别二维码
如何从一张图片上面,识别二维码呢:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | public class ReDecodeThread { public static void encode( final Bitmap bitmap, final ReDecodeThreadResult listener) { if (listener == null ) { return ; } if (bitmap == null ) { listener.onReDecodeResult( null ); return ; } new Thread() { @Override public void run() { try { MultiFormatReader multiFormatReader = new MultiFormatReader(); BitmapLuminanceSource source = new BitmapLuminanceSource(bitmap); BinaryBitmap bitmap1 = new BinaryBitmap( new HybridBinarizer(source)); Result result1 = multiFormatReader.decode(bitmap1); listener.onReDecodeResult(result1.getText()); return ; } catch (NotFoundException e) { e.printStackTrace(); } listener.onReDecodeResult( null ); } }.start(); } public interface ReDecodeThreadResult { void onReDecodeResult(String url); } } |
过程也是很简单,使用MultiFormatReader来分析图片,这里不需要缺人图片的条码格式。
如果分析下源码,就是依次使用每种格式的reader来分析,直到找到合适的为止。
当然回了能够把Bitmap转化成Bitmatrix,然后在分析。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | public final class BitmapLuminanceSource extends LuminanceSource{ private final byte [] luminances; public BitmapLuminanceSource(String path) throws FileNotFoundException { this (loadBitmap(path)); } public BitmapLuminanceSource(Bitmap bitmap) { super (bitmap.getWidth(), bitmap.getHeight()); int width = bitmap.getWidth(); int height = bitmap.getHeight(); int [] pixels = new int [width * height]; bitmap.getPixels(pixels, 0 , width, 0 , 0 , width, height); // In order to measure pure decoding speed, we convert the entire image // to a greyscale array // up front, which is the same as the Y channel of the // YUVLuminanceSource in the real app. luminances = new byte [width * height]; for ( int y = 0 ; y < height; y++) { int offset = y * width; for ( int x = 0 ; x < width; x++) { int pixel = pixels[offset + x]; int r = (pixel >> 16 ) & 0xff ; int g = (pixel >> 8 ) & 0xff ; int b = pixel & 0xff ; if (r == g && g == b) { // Image is already greyscale, so pick any channel. luminances[offset + x] = ( byte ) r; } else { // Calculate luminance cheaply, favoring green. luminances[offset + x] = ( byte ) ((r + g + g + b) >> 2 ); } } } } @Override public byte [] getRow( int y, byte [] row) { if (y < 0 || y >= getHeight()) { throw new IllegalArgumentException( "Requested row is outside the image: " + y); } int width = getWidth(); if (row == null || row.length < width) { row = new byte [width]; } System.arraycopy(luminances, y * width, row, 0 , width); return row; } // Since this class does not support cropping, the underlying byte array // already contains // exactly what the caller is asking for, so give it to them without a copy. @Override public byte [] getMatrix() { return luminances; } private static Bitmap loadBitmap(String path) throws FileNotFoundException { Bitmap bitmap = BitmapFactory.decodeFile(path); if (bitmap == null ) { throw new FileNotFoundException( "Couldn't open " + path); } return bitmap; } } |
5.扫描二维码
扫描二维码,其实比上面只多了一步,就是把camera获取的东西直接转换,然后进行识别。
1 2 3 4 5 6 7 8 9 10 | public void requestPreviewFrame(Handler handler, int message) { if (camera != null && previewing) { previewCallback.setHandler(handler, message); if (useOneShotPreviewCallback) { camera.setOneShotPreviewCallback(previewCallback); } else { camera.setPreviewCallback(previewCallback); } } } |
首先把camera预览的数据放入previewCallback中。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | final class PreviewCallback implements Camera.PreviewCallback public void onPreviewFrame( byte [] data, Camera camera) { Point cameraResolution = configManager.getCameraResolution(); if (!useOneShotPreviewCallback) { camera.setPreviewCallback( null ); } if (previewHandler != null ) { Message message = previewHandler.obtainMessage(previewMessage, cameraResolution.x, cameraResolution.y, data); message.sendToTarget(); previewHandler = null ; } else { Log.d(TAG, "Got preview callback, but no handler for it" ); } } |
可以看到,预览的数据data,回传递过来,然后handler的方式传递出去。
接收data的地方:
1 2 3 4 5 6 7 8 9 10 11 12 | @Override public void handleMessage(Message message) { switch (message.what) { case R.id.decode: //Log.d(TAG, "Got decode message"); decode(( byte []) message.obj, message.arg1, message.arg2); break ; case R.id.quit: Looper.myLooper().quit(); break ; } } |
然后是decode data
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | private void decode( byte [] data, int width, int height) { long start = System.currentTimeMillis(); Result rawResult = null ; //modify here byte [] rotatedData = new byte [data.length]; for ( int y = 0 ; y < height; y++) { for ( int x = 0 ; x < width; x++) rotatedData[x * height + height - y - 1 ] = data[x + y * width]; } int tmp = width; // Here we are swapping, that's the difference to #11 width = height; height = tmp; PlanarYUVLuminanceSource source = CameraManager.get().buildLuminanceSource(rotatedData, width, height); BinaryBitmap bitmap = new BinaryBitmap( new HybridBinarizer(source)); try { rawResult = multiFormatReader.decodeWithState(bitmap); } catch (ReaderException re) { // continue } finally { multiFormatReader.reset(); } if (rawResult != null ) { long end = System.currentTimeMillis(); Log.d(TAG, "Found barcode (" + (end - start) + " ms):\n" + rawResult.toString()); Message message = Message.obtain(activity.getHandler(), R.id.decode_succeeded, rawResult); Bundle bundle = new Bundle(); bundle.putParcelable(DecodeThread.BARCODE_BITMAP, source.renderCroppedGreyscaleBitmap()); message.setData(bundle); //Log.d(TAG, "Sending decode succeeded message..."); message.sendToTarget(); } else { Message message = Message.obtain(activity.getHandler(), R.id.decode_failed); message.sendToTarget(); } } |
当把camera上的图片转换成BinaryBitmap以后,剩下的事情,就更直接从图片识别是一样的。
PlanarYUVLuminanceSource source = CameraManager.get().buildLuminanceSource(rotatedData, width, height);
BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(source));
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