android 二维码生成与识别 Android平台生成二维码并实现扫描 & 识别功能
Joyfulmath 人气:0想了解Android平台生成二维码并实现扫描 & 识别功能的相关内容吗，Joyfulmath在本文为您仔细讲解android 二维码生成与识别的相关知识和一些Code实例，欢迎阅读和指正，我们先划重点：android二维码生成与识别扫描，下面大家一起来学习吧。
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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