1.二維碼的前世今生
“二維條碼/二維碼（2-dimensional bar code）是用某種特定的幾何圖形按一定規律在平面（二維方向上）分布的黑白相間的圖形記錄數據符號信息的；在代碼編制上巧妙地利用構成計算機內部邏輯基礎的“0”、“1”比特流的概念，使用若干個與二進制相對應的幾何形體來表示文字數值信息，通過圖象輸入設備或光電掃描設備自動識讀以實現信息自動處理：它具有條碼技術的一些共性：每種碼制有其特定的字符集；每個字符占有一定的寬度；具有一定的校驗功能等。同時還具有對不同行的信息自動識別功能、及處理圖形旋轉變化點。 [1] ”
上面是百度百科的解釋。既然有二維碼，那么肯定有一維碼。
一維碼。最為常見的就是食品 & 書本后面的條碼。
條碼起源與20世紀40年代，后來在1970年 UPC碼發明，并開始廣泛應用與食品包裝。
具體的介紹可以看百度百科 一維碼。
其實二維碼與一維碼本質上是類似的，就跟一維數組和二維數組一樣。
2.二維碼的java支持庫
為了讓java或者說android方便繼承條碼的功能，google就開發了一個zxing的庫：
https://github.com/zxing/zxing
3.生成二維碼
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() {@Overridepublic 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();}/*** 生成二維碼內容<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 algorithmfor (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 支持很多條碼格式：我們這里使用QR_CODE碼。也就是我們常見的微信里面的二維碼。
我們先來分析下這段代碼：
MultiFormatWriter writer = new MultiFormatWriter();
這個是一個工具類，把所有支持的幾個write寫在里面了。
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);} 這是官方最新支持的格式，具體看引入的jar里面支持的格式。
對與bitmatrix的結果，通過摸個算法，設置每個點白色，或者黑色。
最后創建一張二維碼的圖片。
4.識別二維碼
如何從一張圖片上面，識別二維碼呢：
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() {@Overridepublic 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);}} 過程也是很簡單，使用MultiFormatReader來分析圖片，這里不需要缺人圖片的條碼格式。
如果分析下源碼，就是依次使用每種格式的reader來分析，直到找到合適的為止。
當然回了能夠把Bitmap轉化成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);}}}}@Overridepublic 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.@Overridepublic 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.掃描二維碼
掃描二維碼，其實比上面只多了一步，就是把camera獲取的東西直接轉換，然后進行識別。
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預覽的數據放入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，預覽的數據data，回傳遞過來，然后handler的方式傳遞出去。
接收data的地方：
@Overridepublic 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 herebyte[] 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 #11width = 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();}} 當把camera上的圖片轉換成BinaryBitmap以后，剩下的事情，就更直接從圖片識別是一樣的。
PlanarYUVLuminanceSource source = CameraManager.get().buildLuminanceSource(rotatedData, width, height);
BinaryBitmap bitmap = new BinaryBitmap(new HybridBinarizer(source));
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