Android平台生成二维码并实现扫描 & 识别功能
Android平台生成二维码并实现扫描 & 识别功能
发布时间:2016-12-28 来源:查字典编辑
摘要:1.二维码的前世今生“二维条码/二维码(2-dimensionalbarcode)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...

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

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。

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:

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。

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。

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。

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:

@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

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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