有感于canvas无穷的魅力，使用canvas折腾了一个简单的验证码识别。当然是最简单的验证码识别了，不过准确率还好能达到100%。
首先看一下我们准备识别的验证码，绿色的背景，白色的噪点，黑色的文字（数字0-9），位置和颜色固定，没有旋转，够简单吧。
思路：
1、收集验证码样本，要包括0-9所有的数字。
2、用ps等图像处理工具分析我们将要识别的验证码，得出第一个文字距离左边的位置，字距离顶部的位置，字的宽高以及字与字之间的间隔。这个过程要尽可能的精确，这是我们后期验证码识别是否正确的基本。
3、对验证码样本进行二值化，得出每个数字对应的二值化序列组成素材库。
4、取需要识别的图片的每个数字的二值化序列和素材库中的序列进行比对，比较其相似程度，得出对应的数字。
实现代码：
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
<title>Canvas简单验证码识别</title>
<meta name="description" content="">
<meta name="keywords" content="">
<link href="" rel="stylesheet">
</head>
<body>
<img src="#" id="code" align="absmiddle" alt="">
<button id="recognize">识别</button>
<p>点击图片刷新验证码</p>
<script type="text/javascript">
var OCR = (function(window,document,undefined){
var offsetX,offsetY = 6,fontWidth,fontHeight,gap = 13,source,srcs,kus,codeId,recId;
function init(codeContainerId,recognizeId){
offsetX = 5;
offsetY = 6
fontWidth = 8;
fontHeight = 10;
gap = 13;
source = {};
srcs = ['images/p1.png','images/p2.png','images/p3.png','images/p4.png','images/p5.png','images/p6.png','images/p7.png','images/p8.png','images/p9.png','images/p10.png','images/p11.png','images/p12.png','images/p13.png','images/p14.png'];
kus = [["3","2","2","1"],["4","6","7","5"],["9","8","1","6"],["0","3","5","0"]];
codeId = codeContainerId;
recId = recognizeId;
initSource();
getCode();
addEvent();
}
function initSource(){
for(var i=0;i<4;i++){
(function(){
addSource(srcs[i],kus[i]);
})();
}
}
function getCode(){
var im = document.getElementById("code"),
randPic = srcs[(~~(Math.random()*srcs.length))];
im.src = randPic;
}
function addSource(pic,numArr){
var im = new Image(),
canvas = document.createElement("canvas"),
ctx = canvas.getContext("2d");
im.onload = function(){
canvas.width = this.width;
canvas.height = this.height;
ctx.drawImage(im,0,0);
var imgData = ctx.getImageData(0,0,80,20);
imgData = binaryzationImageData(imgData);
ctx.putImageData(imgData,0,0);
for(var i=1;i<=4;i++){
(function(i){
var imgData = ctx.getImageData(offsetX+gap*(i-1)+fontWidth*(i-1),offsetY,fontWidth,fontHeight);
!source[numArr[i-1]] && (source[numArr[i-1]] = imgData.data.join("").replace(/255/g,"1"));
})(i);
}
}
im.src = pic;
}
function binaryzationImageData(imgData){
for(var i=0;i<imgData.width*imgData.height;i++){
var r = imgData.data[i*4+0],
g = imgData.data[i*4+1],
b = imgData.data[i*4+2];
var gray = 0.299 * r + 0.587 * g + 0.114 * b;
if(gray<=130){
gray = 0;
}else{
gray = 255;
}
imgData.data[i*4+0] = imgData.data[i*4+1] = imgData.data[i*4+2] = gray;
}
return imgData;
}
function recognize(im){
var canvas = document.createElement("canvas"),
ctx = canvas.getContext("2d"),
code = '';
canvas.width = im.width;
canvas.height = im.height;
ctx.drawImage(im,0,0);
for(var i=1;i<=4;i++){
var imgData = ctx.getImageData(offsetX+gap*(i-1)+fontWidth*(i-1),offsetY,fontWidth,fontHeight);
imgData = binaryzationImageData(imgData);
var str = imgData.data.join("").replace(/255/g,"1");
for(var index in source){
if(compare(source[index],str)>=99){
code += index;
break;
}
}
}
alert(code);
}
function getObjectLength(o){
var len = 0;
for(var index in o){
if(o.hasOwnProperty(index)){
len ++;
}
}
return len;
}
function compare(x, y) {
var x = x.split(""),
y = y.split(""),
z = 0,
s = Math.max(x.length,y.length),
a = x.shift(),
b = y.shift();
while(a !== undefined && b !== undefined) {
if (a === b) {
z++;
}
a = x.shift();
b = y.shift();
}
return z/s * 100;
}
function addEvent(){
document.getElementById(recId).onclick = function(){
recognize(document.getElementById(codeId));
}
document.getElementById(codeId).onclick = function(){
getCode();
}
}
return { init : init }
})(window,document);
OCR.init("code","recognize");
</script>
</body>
</html>