136 lines
3.9 KiB
C++
136 lines
3.9 KiB
C++
/* 程序名：singlefeature.c
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功能：分总程序：读入图像文件，得出单个文件的特征值
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*/
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#include <stdlib.h>
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#include <stdio.h>
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#include <math.h>
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#include <cv.h>
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#include <highgui.h>
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#include "Point.h"
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#include "FreeImage.h" //用于读gif的图像
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#include<io.h> //下面的5个用于读取文件夹下的所有文件名
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#include<vector>
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#include<iostream>
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using namespace std;
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#include <string.h>
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#include <direct.h>
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#include"Thinner.h"
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/*各种声明*/
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void getFiles(string path, vector<string>& files );//读取文件名下所有文件
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char* getType(char fileName[], char type[]); //获取图像类型
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int* binary(IplImage* img,int bithro); //二值化图像
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int outlinefeature(IplImage* imglk,int feature[ ][50]);//计算图像的轮廓特征值
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IplImage* Cjbsb(IplImage* img,IplImage* imgjbsb,int jbwhite,int jbblack);//图像角标识别
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IplImage* gif2ipl(const char* filename); //读取gif的外部函数
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IplImage* singlefeature(char* path,int feature[ ][50],int flag){
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//定义变量
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IplImage* img = 0; //原图
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IplImage* imglk = 0; //轮廓图
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IplImage* imggj = 0; //骨架图
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IplImage* imgjbsb = 0; //角标识别图
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IplImage* imgbj = 0; //只提取笔记部分的图像
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char imgtype[10]; //判断图像类型
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int height,width,step,channels;
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uchar *data;
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int *black; //用于返回图像每行黑像素的个数
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//int feature[50][50]={0}; //特征值初始化
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getType(path, imgtype);
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if(strcmp(".gif", imgtype) == 0)
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{
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IplImage* Iplimg=gif2ipl(path); //gif 转 rgb 三维
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img=cvCreateImage(cvGetSize(Iplimg),Iplimg->depth,1);
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cvCvtColor(Iplimg,img,CV_RGB2GRAY); //rgb 转灰度
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cvReleaseImage(&Iplimg); //释放临时图像的内存
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cvFlip(img,NULL, 0); //由于得到的灰度图是翻转的，所以再翻转回来
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}
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else if(strcmp(".jpg", imgtype) == 0 || strcmp(".png", imgtype) == 0)
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img=cvLoadImage(path,0);
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else
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return NULL;
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if(!img)
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{
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printf("Could not load image file: %s\n",path);
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exit(0);
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}
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// 获取图像信息
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height = img->height;
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width = img->width;
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step = img->widthStep;
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channels = img->nChannels;
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data = (uchar *)img->imageData;
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//开始处理
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//图像放大
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IplImage* imgbig = 0; //原图的放大图
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CvSize dst_cvsize; //目标图像的大小
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float scale=1;
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if(width<850){
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scale=(float)850/width;
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dst_cvsize.width=850;
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dst_cvsize.height=(int)(height*scale);
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}
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else
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{
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dst_cvsize.width=width;
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dst_cvsize.height=height;
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}
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imgbig=cvCreateImage(dst_cvsize,img->depth,img->nChannels);
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cvResize(img,imgbig,CV_INTER_LINEAR); // CV_INTER_NN - 最近邻插值,
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//CV_INTER_LINEAR - 双线性插值 (缺省使用),
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//CV_INTER_AREA - 使用象素关系重采样。当图像缩小时候，该方法可以避免波纹出现。
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//CV_INTER_CUBIC - 立方插值.
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//二值化
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int bithro=230; //输入二值化的阈值 (0--255)
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black=binary(imgbig,bithro); //二值化，并统计黑像素的个数，返回每行黑像素的个数(black)
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//cvNamedWindow("二值化结果图",CV_WINDOW_AUTOSIZE); //显示图像
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//cvShowImage("二值化结果图",img);
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//printf("二值化求解完成！！\n");
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//角标识别,裁切出图像
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int jbwhite=5,jbblack=4;
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imgjbsb = cvCreateImage(cvGetSize(imgbig),imgbig->depth,imgbig->nChannels);
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imgbj=Cjbsb(imgbig,imgjbsb,jbwhite,jbblack); //返回文字的笔迹部分
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//存储裁剪后的图像
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//D:/xiangmu/Img/imgjiaobiao/010211100059x/0359.gif
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char isavePath[200]="E";
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//此处需要新建一个新建文件夹的选项
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string name=path;
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strcat(isavePath, name.substr(1, 39).c_str());
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string md="mkdir ";
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md += isavePath;
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//组合出新名字
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strcat(isavePath, name.substr(40, 5).c_str());
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strcat(isavePath, ".jpg");
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//创建文件夹
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if(flag) system(md.c_str());
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//保存图像
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cvSaveImage(isavePath,imgbj);
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cvReleaseImage(&imgbig);
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cvReleaseImage(&img );
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cvReleaseImage(&imgbj );
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cvDestroyAllWindows();
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cout<<".";
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return imggj;
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}
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