完善目录结构

完善了目录结构，添加了以前的web段com组件调用的代码（在/测试目录下）（部署没有使用到）

测试/单独功能测试/0-DLL测试（实际没有部署）/dll-goal无数据库/singlefeature.cpp

@@ -0,0 +1,163 @@
+/* 	程序名：singlefeature.c
+功能：分总程序：读入图像文件，得出单个文件的特征值
+*/
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <cv.h>
+#include <highgui.h>
+#include "Point.h"
+#include<io.h>
+#include<vector>
+#include<iostream>
+#include <string.h>
+#include <direct.h>
+#include"Thinner.h"
+
+using namespace std;
+/*各种声明*/                            
+int*		binary(IplImage*  img, int bithro);  //二值化图像      
+int			outlinefeature(IplImage* imglk, int feature[][50]);//计算图像的轮廓特征值                         
+IplImage*	Cjbsb(IplImage* img, IplImage* imgjbsb, int jbwhite, int jbblack);//图像角标识别
+
+IplImage* singlefeature(char* path, int feature[][50]){
+	//定义变量
+	IplImage* img = 0;          //原图
+	IplImage* imglk = 0;        //轮廓图
+	IplImage* imggj = 0;        //骨架图
+	IplImage* imgjbsb = 0;      //角标识别图
+	IplImage* imgbj = 0;        //只提取笔记部分的图像
+	IplImage* imgbjhf = 0;      //为文字区域画上方格
+	IplImage* imgwzbj = 0;      //为文字区域标出是否为文字（文字标记）
+
+	int height, width, step, channels;
+	uchar *data;
+
+	int i, j;
+	int *black;                 //用于返回图像每行黑像素的个数
+	//int feature[50][50]={0};    //特征值初始化
+
+	img = cvLoadImage(path, 0);
+
+	/* 获取图像信息*/
+	height = img->height;
+	width = img->width;
+	step = img->widthStep;
+	channels = img->nChannels;
+	data = (uchar *)img->imageData;
+
+	/*开始处理*/
+
+	/*图像放大*/
+	IplImage* imgbig = 0;          //原图的放大图
+	CvSize dst_cvsize;             //目标图像的大小
+	float scale = 1;
+	if (width<840){
+		scale = (float)840 / width;
+		dst_cvsize.width = 840;
+		dst_cvsize.height = (int)(height*scale);
+	}
+	else
+	{
+		dst_cvsize.width = width;
+		dst_cvsize.height = height;
+	}
+
+	imgbig = cvCreateImage(dst_cvsize, img->depth, img->nChannels);
+	cvResize(img, imgbig, CV_INTER_LINEAR);	// CV_INTER_NN - 最近邻插值,
+	//CV_INTER_LINEAR - 双线性插值 (缺省使用),
+	//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。
+	//CV_INTER_CUBIC - 立方插值.
+
+	/*二值化*/
+	int bithro = 230;                              //输入二值化的阈值   (0--255)
+	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)
+	//cvNamedWindow("二值化结果图",CV_WINDOW_AUTOSIZE);                   //显示图像
+	//cvShowImage("二值化结果图",img); 
+	//printf("二值化求解完成！！\n");
+
+
+
+	/*角标识别*/
+	int jbwhite = 5, jbblack = 4;
+	imgjbsb = cvCreateImage(cvGetSize(imgbig), imgbig->depth, imgbig->nChannels);
+	imgbj = Cjbsb(imgbig, imgjbsb, jbwhite, jbblack);                              //返回文字的笔迹部分
+
+
+	/*计算骨架图*/
+	imggj = cvCreateImage(cvGetSize(imgbj), imgbj->depth, imgbj->nChannels);   //复制
+	cvCopy(imgbj, imggj, NULL);
+	uchar *gjdata = (uchar *)imggj->imageData;
+
+	beforethin(gjdata, gjdata, imggj->width, imggj->height);
+
+	for (j = 0; j<imggj->height; j++)
+	{ //取值范围转到0--1  
+
+		for (i = 0; i<imggj->width; i++)
+		{
+			if (gjdata[j*imggj->widthStep + i] == 255)
+				gjdata[j*imggj->widthStep + i] = 1;
+		}
+	}
+	ThinnerRosenfeld(imggj->imageData, imggj->height, imggj->width);
+
+	for (j = 0; j<imggj->height; j++)
+	{//取值范围转到0--255,反转过来
+		for (i = 0; i<imggj->width; i++)
+		{
+			if (gjdata[j*imggj->widthStep + i] == 1)
+				gjdata[j*imggj->widthStep + i] = 0;
+			else
+				gjdata[j*imggj->widthStep + i] = 255;
+		}
+	}
+
+	//保存图像 应先生成图像文件名
+	/*
+	char processPic[100]="E:/imggj/";
+	char *namePic=new char[20];
+	bool flag=false;
+	string xuehao=path,kaoshihao=path;
+	int num_iter=sizeof(path);
+	for(int iter=0;iter<num_iter;iter++)
+	{
+	if(path[iter]=='x')
+	{
+	flag=true;
+	break;
+	}
+	}
+	if(flag)
+	{
+	xuehao=xuehao.substr(27,13);
+	kaoshihao=kaoshihao.substr(40,5);
+	}else
+	{
+	xuehao=xuehao.substr(27,12);
+	kaoshihao=kaoshihao.substr(39,5);
+	}
+	strcat(processPic,xuehao.c_str());
+	_mkdir(processPic);
+	strcat(processPic,kaoshihao.c_str());
+	strcat(processPic,".jpg");
+	cvSaveImage(processPic,imggj);
+	*/
+	/*计算骨架特征徝*/
+	outlinefeature(imggj, feature);   //特征值占48*48的右上三角形，feature调用返回
+	//cvWaitKey(0);
+
+	/*释放内存*/
+	cvReleaseImage(&imgbig);
+	cvReleaseImage(&img);
+	cvReleaseImage(&imgbj);
+	cvReleaseImage(&imglk);
+	cvReleaseImage(&imgjbsb);
+	cvReleaseImage(&imgbjhf);
+	cvReleaseImage(&imgwzbj);
+	cvDestroyAllWindows();
+
+	return imggj;
+}
+
+