1. 缩小尺寸：将图像缩小到8*8的尺寸，总共64个像素。这一步的作用是去除图像的细节，只保留结构/明暗等基本信息，摒弃不同尺寸/比例带来的图像差异；
注：实际操作时，采取了两种尺寸作对比（10*10，100*100）尺寸再大的话就会性能影响就会较大了，我实现了两种，目的是为了展示怎么设定不同尺寸。
2. 简化色彩：将缩小后的图像，转为64级灰度，即所有像素点总共只有64种颜色；
注：关于多少灰度级的问题，我并没有太在意，采取了一个合适的RGB to GRAY 算法就好，个人理解
3. 计算平均值：计算所有64个像素的灰度平均值；
4. 比较像素的灰度：将每个像素的灰度，与平均值进行比较，大于或等于平均值记为1，小于平均值记为0；
5. 计算哈希值：将上一步的比较结果，组合在一起，就构成了一个64位的整数，这就是这张图像的指纹。组合的次序并不重要，只要保证所有图像都采用同样次序就行了；
6. 得到指纹以后，就可以对比不同的图像
GetSimilarity.h
//
// GetSimilarity.h
// imgsimlartest
//
// Created by test on 16/3/3.
// Copyright © 2016年 com.facishare.CoreTest. All rights reserved.
//
#import <Foundation/Foundation.h>
#import <UIKit/UIKit.h>
typedef double Similarity;
@interface GetSimilarity : NSObject
- (void)setImgWithImgA:(UIImage*)imgA ImgB:(UIImage*)imgB;//设置需要对比的图片
- (void)setImgAWidthImg:(UIImage*)img;
- (void)setImgBWidthImg:(UIImage*)img;
- (Similarity)getSimilarityValue; //获取相似度
+ (Similarity)getSimilarityValueWithImgA:(UIImage*)imga ImgB:(UIImage*)imgb;//类方法
@end
GetSimilarity.m
//
// GetSimilarity.m
// imgsimlartest
//
// Created by test on 16/3/3.
// Copyright © 2016年 com.facishare.CoreTest. All rights reserved.
//
#import "GetSimilarity.h"
#define ImgSizeA 10
#define ImgSizeB 100
typedef enum workday
{
SizeA,
SizeB,
}GetSimilarityType;
@interface GetSimilarity()
@property (nonatomic,assign) Similarity similarity;
@property (nonatomic,strong) UIImage *imga;
@property (nonatomic,strong) UIImage *imgb;
@end
@implementation GetSimilarity
- (instancetype)init
{
self = [super init];
if (self) {
self.imga = [[UIImage alloc]init];
self.imgb = [[UIImage alloc]init];
}
return self;
}
- (void)setImgWithImgA:(UIImage*)imgA ImgB:(UIImage*)imgB
{
_imga = imgA;
_imgb = imgB;
}
- (void)setImgAWidthImg:(UIImage*)img
{
self.imga = img;
}
- (void)setImgBWidthImg:(UIImage*)img
{
self.imgb = img;
}
- (Similarity)getSimilarityValue
{
self.similarity = MAX([self getSimilarityValueWithType:SizeA], [self getSimilarityValueWithType:SizeB]);
return self.similarity;
}
+ (Similarity)getSimilarityValueWithImgA:(UIImage *)imga ImgB:(UIImage *)imgb
{
GetSimilarity * getSimilarity = [[GetSimilarity alloc]init];
[getSimilarity setImgWithImgA:imga ImgB:imgb];
return [getSimilarity getSimilarityValue];
}
- (Similarity)getSimilarityValueWithType:(GetSimilarityType)type;//
{
int cursize = (type == SizeA ? ImgSizeA : ImgSizeB);
int ArrSize = cursize * cursize + 1,a[ArrSize],b[ArrSize],i,j,grey,sum = 0;
CGSize size = {cursize,cursize};
UIImage * imga = [self reSizeImage:self.imga toSize:size];
UIImage * imgb = [self reSizeImage:self.imgb toSize:size];//缩小图片尺寸
a[ArrSize] = 0;
b[ArrSize] = 0;
CGPoint point;
for (i = 0 ; i < cursize; i++) {//计算a的灰度
for (j = 0; j < cursize; j++) {
point.x = i;
point.y = j;
grey = ToGrey([self UIcolorToRGB:[self colorAtPixel:point img:imga]]);
a[cursize * i + j] = grey;
a[ArrSize] += grey;
}
}
a[ArrSize] /= (ArrSize - 1);//灰度平均值
for (i = 0 ; i < cursize; i++) {//计算b的灰度
for (j = 0; j < cursize; j++) {
point.x = i;
point.y = j;
grey = ToGrey([self UIcolorToRGB:[self colorAtPixel:point img:imgb]]);
b[cursize * i + j] = grey;
b[ArrSize] += grey;
}
}
b[ArrSize] /= (ArrSize - 1);//灰度平均值
for (i = 0 ; i < ArrSize ; i++)//灰度分布计算
{
a[i] = (a[i] < a[ArrSize] ? 0 : 1);
b[i] = (b[i] < b[ArrSize] ? 0 : 1);
}
ArrSize -= 1;
for (i = 0 ; i < ArrSize ; i++)
{
sum += (a[i] == b[i] ? 1 : 0);
}
return sum * 1.0 / ArrSize;
}
- (UIImage *)reSizeImage:(UIImage *)image toSize:(CGSize)reSize//重新设定图片尺寸
{
UIGraphicsBeginImageContext(CGSizeMake(reSize.width, reSize.height));
[image drawInRect:CGRectMake(0, 0, reSize.width, reSize.height)];
UIImage *reSizeImage = UIGraphicsGetImageFromCurrentImageContext();
UIGraphicsEndImageContext();
return reSizeImage;
}
unsigned int ToGrey(unsigned int rgb)//RGB计算灰度
{
unsigned int blue = (rgb & 0x000000FF) >> 0;
unsigned int green = (rgb & 0x0000FF00) >> 8;
unsigned int red = (rgb & 0x00FF0000) >> 16;
return ( red*38 + green * 75 + blue * 15 )>>7;
}
- (unsigned int)UIcolorToRGB:(UIColor*)color//UIColor转16进制RGB
{
unsigned int RGB,R,G,B;
RGB = R = G = B = 0x00000000;
CGFloat r,g,b,a;
[color getRed:&r green:&g blue:&b alpha:&a];
R = r * 256 ;
G = g * 256 ;
B = b * 256 ;
RGB = (R << 16) | (G << 8) | B ;
return RGB;
}
- (UIColor *)colorAtPixel:(CGPoint)point img:(UIImage*)img{//获取指定point位置的RGB
// Cancel if point is outside image coordinates
if (!CGRectContainsPoint(CGRectMake(0.0f, 0.0f, img.size.width, img.size.height), point)) { return nil; }
NSInteger pointX = trunc(point.x);
NSInteger pointY = trunc(point.y);
CGImageRef cgImage = img.CGImage;
NSUInteger width = img.size.width;
NSUInteger height = img.size.height;
int bytesPerPixel = 4;
int bytesPerRow = bytesPerPixel * 1;
NSUInteger bitsPerComponent = 8;
unsigned char pixelData[4] = { 0, 0, 0, 0 };
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
CGContextRef context = CGBitmapContextCreate(pixelData, 1, 1, bitsPerComponent, bytesPerRow, colorSpace, kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big);
CGColorSpaceRelease(colorSpace);
CGContextSetBlendMode(context, kCGBlendModeCopy);
// Draw the pixel we are interested in onto the bitmap context
CGContextTranslateCTM(context, -pointX, pointY-(CGFloat)height);
CGContextDrawImage(context, CGRectMake(0.0f, 0.0f, (CGFloat)width, (CGFloat)height), cgImage);
CGContextRelease(context);
// Convert color values [0..255] to floats [0.0..1.0]
CGFloat red = (CGFloat)pixelData[0] / 255.0f;
CGFloat green = (CGFloat)pixelData[1] / 255.0f;
CGFloat blue = (CGFloat)pixelData[2] / 255.0f;
CGFloat alpha = (CGFloat)pixelData[3] / 255.0f;
return [UIColor colorWithRed:red green:green blue:blue alpha:alpha];
}
@end