#include "images.h" uint8 l_border[MT9V03X_H];//左线数组 uint8 r_border[MT9V03X_H];//右线数组 uint8 center_line[MT9V03X_H];//中线数组 /*变量声明*/ //uint8 original_image[MT9V03X_H][MT9V03X_W]; uint8 bin_image[MT9V03X_H][MT9V03X_W];//图像数组 uint8 image_thereshold_last = 0;// uint8 image_thereshold;//图像分割阈值 //------------------------------------------------------------------------------------------------------------------ // @函数功能 求绝对值 // @函数返回 绝对值 //------------------------------------------------------------------------------------------------------------------ int my_abs(int value) { if(value>=0) return value; else return -value; } //数值范围限制 int16 limit_a_b(int16 x, int a, int b) { if(x<a) x = a; if(x>b) x = b; return x; } //------------------------------------------------------------------------------------------------------------------ // @函数功能 求x,y中的最小值 // @函数返回 两值中的最小值 //------------------------------------------------------------------------------------------------------------------ int16 limit1(int16 x, int16 y) { if (x > y) return y; else if (x < -y) return -y; else return x; } //------------------------------------------------------------------------------------------------------------------ // @函数功能 获得一副灰度图像 // @函数返回 灰度图像数组original_image //------------------------------------------------------------------------------------------------------------------ void Get_image(uint8(*mt9v03x_image)[MT9V03X_W]) { uint8 i = 0, j = 0; for (i = 0; i < MT9V03X_H; i += 1) { for (j = 0; j <MT9V03X_W; j += 1) { bin_image[i][j] = mt9v03x_image[i][j]; } } } //将原始图像复制到bin_image数组 //------------------------------------------------------------------------------------------------------------------ // @函数功能 大津法求动态阈值 // @函数返回 动态阈值Threshold //------------------------------------------------------------------------------------------------------------------ uint8 OtsuThreshold(uint8 *image) { uint8 Pixel_Max = 0; uint8 Pixel_Min = 255; //uint16 width = MT9V03X_W / use_num; //uint16 height = MT9V03X_H / use_num; int pixelCount[GrayScale]; //各像素GrayScale的个数pixelCount 一维数组 float pixelPro[GrayScale]; //各像素GrayScale所占百分比pixelPro 一维数组 int16 i = 0; int16 j = 0; int16 pixelSum = MT9V03X_W * MT9V03X_H / 4; //pixelSum是获取总的图像像素个数的1/4，相应下面轮询时高和宽都是以2为单位自增 uint8 threshold = 0; uint8* data = image; //指向像素数据的指针 for(i = 0;i < GrayScale;i++) { pixelCount[i] = 0; pixelPro[i] = 0; } uint32 gray_sum = 0; //统计灰度图中每个像素在整幅图像中的个数 for(i = 0;i < MT9V03X_H;i += 2) { for(j = 0;j < MT9V03X_W; j += 2) { pixelCount[(int)data[i * MT9V03X_W + j]]++; //将当前的点的像素值作为计数数组的下标 gray_sum += (int)data[i * MT9V03X_W + j]; //灰度值总和 if(data[i * MT9V03X_W + j] > Pixel_Max) { Pixel_Max = data[i * MT9V03X_W + j]; } if(data[i * MT9V03X_W + j] < Pixel_Min) { Pixel_Min = data[i * MT9V03X_W + j]; } } } //计算每个像素值的点在整幅图像中的比例 for(i = Pixel_Min;i < Pixel_Max;i++) { pixelPro[i] = (float)pixelCount[i] / pixelSum; } //遍历灰度值 float w0,w1,u0tmp,u1tmp,u0,u1,deltaTmp,deltaMax = 0; w0 = w1 = u0tmp = u1tmp = u0 = u1 = deltaTmp = 0; for(j = Pixel_Min;j < Pixel_Max;j++) { w0 += pixelPro[j]; //背景部分每个灰度值的像素点所占比例之和 即背景部分的比例 u0tmp += j * pixelPro[j]; //背景部分 每个灰度值的点的比例 *灰度值 w1 = 1 - w0; u1tmp = gray_sum / pixelSum-u0tmp; u0 = u0tmp / w0; //背景平均灰度 u1 = u1tmp / w1; //前景平均灰度 deltaTmp = (float)(w0 * w1 * (u0 - u1) * (u0 - u1)); if(deltaTmp > deltaMax) { deltaMax = deltaTmp; threshold = (uint8)j; } if(deltaTmp < deltaMax) { break; } } //限幅 if(threshold > 25 && threshold < 235) { image_thereshold_last = threshold; } else { threshold = image_thereshold_last; } return threshold; } //------------------------------------------------------------------------------------------------------------------ // @函数功能 图像二值化，大津法 // @函数返回 二值化图像数组bin_image //------------------------------------------------------------------------------------------------------------------ void turn_to_bin(void) { uint8 i,j; image_thereshold = OtsuThreshold(bin_image[0]); //ips114_show_int(189,0,image_thereshold,5); for(i = 0;i < MT9V03X_H;i++) { for(j = 0;j < MT9V03X_W;j++) { if(bin_image[i][j] > image_thereshold) { bin_image[i][j] = 255; } else { bin_image[i][j] = 0; } } } /* for(i = 40;i < MT9V03X_H;i++) { for(j = 0;j < MT9V03X_W;j++) { if(bin_image[i][j] < image_thereshold) { bin_image[i][j] = 0; } else { bin_image[i][j] =255; } } }*/ } //------------------------------------------------------------------------------------------------------------------ // @函数功能 寻找两个边界的边界点作为八邻域循环的起始点 // @参数说明 输入任意行数 // @函数返回 无 //------------------------------------------------------------------------------------------------------------------ uint8 start_point_l[2] = { 0 };//左边起点的x，y值 uint8 start_point_r[2] = { 0 };//右边起点的x，y值 uint8 get_start_point(uint8 start_row) { uint8 i = 0,j = MT9V03X_W/2,l_found = 0,r_found = 0,num = 0; //清零 start_point_l[0] = 0;//左x start_point_l[1] = 0;//左y start_point_r[0] = 0;//右x start_point_r[1] = 0;//右y //大致定位白线 for(num = 0;num < MT9V03X_W/2 - 15;num = num + 10) { if(bin_image[start_row][j + num] == 255) { j = j + num; break; } if(bin_image[start_row][j - num] == 255) { j = j - num; break; } } //从中间往左边，先找起点 for (i = j; i > border_min; i--) { start_point_l[0] = i;//x start_point_l[1] = start_row;//y if (bin_image[start_row][i] == 255 && bin_image[start_row][i - 1] == 0) { //printf("找到左边起点image[%d][%d]\n", start_row,i); l_found = 1; break; } } for (i = j; i < border_max; i++) { start_point_r[0] = i;//x start_point_r[1] = start_row;//y if (bin_image[start_row][i] == 255 && bin_image[start_row][i + 1] == 0) { //printf("找到右边起点image[%d][%d]\n",start_row, i); r_found = 1; break; } } if(l_found&&r_found) { return 1; } else { //printf("未找到起点\n"); return 0; } } //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- // @函数功能 八邻域正式开始找右边点的函数，左右线一次性找完。 Tip:特别注意，不要拿宏定义名字作为输入参数，否则数据可能无法传递过来 // @参数说明 // break_flag_r 最多需要循环的次数 // (*image)[image_w] 需要进行找点的图像数组，必须是二值图,填入数组名称即可 // *l_stastic 统计左边数据，用来输入初始数组成员的序号和取出循环次数 // *r_stastic 统计右边数据，用来输入初始数组成员的序号和取出循环次数 // l_start_x 左边起点横坐标 // l_start_y 左边起点纵坐标 // r_start_x 右边起点横坐标 // r_start_y 右边起点纵坐标 // hightest 循环结束所得到的最高高度 // @函数返回 无 // @备 注： //example：search_l_r((uint16)USE_num,image,&data_stastics_l, &data_stastics_r,start_point_l[0],start_point_l[1], start_point_r[0], start_point_r[1],&hightest); //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- #define USE_num MT9V03X_H*3 //定义找点的数组成员个数按理说300个点能放下，但是有些特殊情况确实难顶，多定义了一点 //存放点的x，y坐标 uint16 points_l[(uint16)USE_num][2] = { { 0 } };//左线 uint16 points_r[(uint16)USE_num][2] = { { 0 } };//右线 uint16 dir_r[(uint16)USE_num] = { 0 };//用来存储右边生长方向 uint16 dir_l[(uint16)USE_num] = { 0 };//用来存储左边生长方向 uint16 data_stastics_l = 0;//统计左边找到点的个数 uint16 data_stastics_r = 0;//统计右边找到点的个数 uint8 hightest = 0;//最高点 void search_l_r(uint16 break_flag, uint8(*image)[MT9V03X_W], uint16 *l_stastic, uint16 *r_stastic, uint8 l_start_x, uint8 l_start_y, uint8 r_start_x, uint8 r_start_y, uint8*hightest) { uint8 i = 0, j = 0; //左边变量 uint8 search_filds_l[8][2] = { { 0 } }; uint8 index_l = 0; uint8 temp_l[8][2] = { { 0 } }; uint8 center_point_l[2] = { 0 }; uint16 l_data_statics;//统计左边 //定义八个邻域 static int8 seeds_l[8][2] = {{0,1},{-1,1},{-1,0},{-1,-1},{0,-1},{1,-1},{1,0},{1,1},}; //{-1,-1} {0,-1} {+1,-1} //{-1, 0} {+1, 0} //{-1,+1} {0,+1} {+1,+1} //顺时针 //右边变量 uint8 search_filds_r[8][2] = { { 0 } }; uint8 center_point_r[2] = { 0 };//中心坐标点 uint8 index_r = 0;//索引下标 uint8 temp_r[8][2] = { { 0 } }; uint16 r_data_statics;//统计右边 //定义八个邻域 static int8 seeds_r[8][2] = { {0,1},{1,1},{1,0}, {1,-1},{0,-1},{-1,-1}, {-1,0},{-1,1}, }; //{-1,-1} {0,-1} {+1,-1}, //{-1, 0} {+1, 0} //{-1,+1} {0,+1} {+1,+1} //这个是逆时针 l_data_statics = *l_stastic;//统计找到了多少个点，方便后续把点全部画出来 r_data_statics = *r_stastic;//统计找到了多少个点，方便后续把点全部画出来 //第一次更新坐标点 将找到的起点值传进来 center_point_l[0] = l_start_x;//x center_point_l[1] = l_start_y;//y center_point_r[0] = r_start_x;//x center_point_r[1] = r_start_y;//y //开启邻域循环 while (break_flag--) { //左边 for (i = 0; i < 8; i++)//传递8F坐标 { search_filds_l[i][0] = center_point_l[0] + seeds_l[i][0];//x search_filds_l[i][1] = center_point_l[1] + seeds_l[i][1];//y } //中心坐标点填充到已经找到的点内 points_l[l_data_statics][0] = center_point_l[0];//x points_l[l_data_statics][1] = center_point_l[1];//y l_data_statics++;//索引加一 //右边 for (i = 0; i < 8; i++)//传递8F坐标 { search_filds_r[i][0] = center_point_r[0] + seeds_r[i][0];//x search_filds_r[i][1] = center_point_r[1] + seeds_r[i][1];//y } //中心坐标点填充到已经找到的点内 points_r[r_data_statics][0] = center_point_r[0];//x points_r[r_data_statics][1] = center_point_r[1];//y index_l = 0;//先清零，后使用 for (i = 0; i < 8; i++) { temp_l[i][0] = 0;//先清零，后使用 temp_l[i][1] = 0;//先清零，后使用 } //左边判断 for (i = 0; i < 8; i++) { if (image[search_filds_l[i][1]][search_filds_l[i][0]] == 0 && image[search_filds_l[(i + 1) & 7][1]][search_filds_l[(i + 1) & 7][0]] == 255) { temp_l[index_l][0] = search_filds_l[(i)][0]; temp_l[index_l][1] = search_filds_l[(i)][1]; index_l++; dir_l[l_data_statics - 1] = (i);//记录生长方向 } if (index_l) { //更新坐标点 center_point_l[0] = temp_l[0][0];//x center_point_l[1] = temp_l[0][1];//y for (j = 0; j < index_l; j++) { if (center_point_l[1] > temp_l[j][1]) { center_point_l[0] = temp_l[j][0];//x center_point_l[1] = temp_l[j][1];//y } } } } if ((points_r[r_data_statics][0]== points_r[r_data_statics-1][0]&& points_r[r_data_statics][0] == points_r[r_data_statics - 2][0] && points_r[r_data_statics][1] == points_r[r_data_statics - 1][1] && points_r[r_data_statics][1] == points_r[r_data_statics - 2][1]) ||(points_l[l_data_statics-1][0] == points_l[l_data_statics - 2][0] && points_l[l_data_statics-1][0] == points_l[l_data_statics - 3][0] && points_l[l_data_statics-1][1] == points_l[l_data_statics - 2][1] && points_l[l_data_statics-1][1] == points_l[l_data_statics - 3][1])) { //printf("三次进入同一个点，退出\n"); break; } if (my_abs(points_r[r_data_statics][0] - points_l[l_data_statics - 1][0]) < 2 && my_abs(points_r[r_data_statics][1] - points_l[l_data_statics - 1][1] < 2)) { //printf("\n左右相遇退出\n"); *hightest = (points_r[r_data_statics][1] + points_l[l_data_statics - 1][1]) >> 1;//取出最高点 //printf("\n在y=%d处退出\n",*hightest); break; } if ((points_r[r_data_statics][1] < points_l[l_data_statics - 1][1])) { //printf("\n如果左边比右边高了，左边等待右边\n"); continue;//如果左边比右边高了，左边等待右边 } if (dir_l[l_data_statics - 1] == 7 && (points_r[r_data_statics][1] > points_l[l_data_statics - 1][1]))//左边比右边高且已经向下生长了 { //printf("\n左边开始向下了，等待右边，等待中... \n"); center_point_l[0] = points_l[l_data_statics - 1][0];//x center_point_l[1] = points_l[l_data_statics - 1][1];//y l_data_statics--; } r_data_statics++;//索引加一 index_r = 0;//先清零，后使用 for (i = 0; i < 8; i++) { temp_r[i][0] = 0;//先清零，后使用 temp_r[i][1] = 0;//先清零，后使用 } //右边判断 for (i = 0; i < 8; i++) { if (image[search_filds_r[i][1]][search_filds_r[i][0]] == 0 && image[search_filds_r[(i + 1) & 7][1]][search_filds_r[(i + 1) & 7][0]] == 255) { temp_r[index_r][0] = search_filds_r[(i)][0]; temp_r[index_r][1] = search_filds_r[(i)][1]; index_r++;//索引加一 dir_r[r_data_statics - 1] = (i);//记录生长方向 //printf("dir[%d]:%d\n", r_data_statics - 1, dir_r[r_data_statics - 1]); } if (index_r) { //更新坐标点 center_point_r[0] = temp_r[0][0];//x center_point_r[1] = temp_r[0][1];//y for (j = 0; j < index_r; j++) { if (center_point_r[1] > temp_r[j][1]) { center_point_r[0] = temp_r[j][0];//x center_point_r[1] = temp_r[j][1];//y } } } } } //取出循环次数 *l_stastic = l_data_statics; *r_stastic = r_data_statics; } //------------------------------------------------------------------------------------------------------------------ // @函数功能 从八邻域边界里提取需要的左边线 // @参数说明 total_L ：找到的点的总数 // @函数返回 左边线数组l_border //------------------------------------------------------------------------------------------------------------------ uint16 border_to_edge_l[MT9V03X_H];//存放左边border和edge的映射关系的数组 void get_left(uint16 total_L) { uint8 i = 0; uint16 j = 0; uint8 h = 0; //初始化 for (i = 0;i<MT9V03X_H;i++) { l_border[i] = border_min; } h = MT9V03X_H - 2; //左边 for (j = 0; j < total_L; j++) { //printf("%d\n", j); if (points_l[j][1] == h) { l_border[h] = points_l[j][0]+1; border_to_edge_l[h] = j; } else continue; //每行只取一个点，没到下一行就不记录 h--; if (h == 0) { break;//到最后一行退出 } } } //------------------------------------------------------------------------------------------------------------------ // @函数功能 从八邻域边界里提取需要的右边线 // @参数说明 total_R ：找到的点的总数 // @函数返回 右边线数组r_border //------------------------------------------------------------------------------------------------------------------ uint16 border_to_edge_r[MT9V03X_H];//存放右边border和edge的映射关系的数组 void get_right(uint16 total_R) { uint8 i = 0; uint16 j = 0; uint8 h = 0; for (i = 0; i < MT9V03X_H; i++) { r_border[i] = border_max;//右边线初始化放到最右边，左边线放到最左边，这样八邻域闭合区域外的中线就会在中间，不会干扰得到的数据 } h = MT9V03X_H - 2; //右边 for (j = 0; j < total_R; j++) { if (points_r[j][1] == h) { r_border[h] = points_r[j][0] - 1; border_to_edge_r[h] = j; } else continue;//每行只取一个点，没到下一行就不记录 h--; if (h == 0)break;//到最后一行退出 } } //------------------------------------------------------------------------------------------------------------------ // @函数功能 滤波减少噪声 // @函数返回 经过滤波的图像数组bin_image //------------------------------------------------------------------------------------------------------------------ #define threshold_max 255*5//定义膨胀的阈值区间 #define threshold_min 255*2//定义腐蚀的阈值区间 void image_filter(uint8(*bin_image)[MT9V03X_W])//形态学滤波，膨胀和腐蚀 { uint16 i, j; uint32 num = 0; for (i = 1; i < MT9V03X_H - 1; i++) { for (j = 1; j < (MT9V03X_W - 1); j++) { //统计八个方向的像素值 num = bin_image[i - 1][j - 1] + bin_image[i - 1][j] + bin_image[i - 1][j + 1] + bin_image[i][j - 1] + bin_image[i][j + 1] + bin_image[i + 1][j - 1] + bin_image[i + 1][j] + bin_image[i + 1][j + 1]; if (num >= threshold_max && bin_image[i][j] == 0) { bin_image[i][j] = 255;//白 } if (num <= threshold_min && bin_image[i][j] == 255) { bin_image[i][j] = 0;//黑 } } } } //------------------------------------------------------------------------------------------------------------------ // @函数功能 给图像画一个黑框 // @函数返回 带有黑框的图像数组bin_image //------------------------------------------------------------------------------------------------------------------ void image_draw_rectan(uint8(*image)[MT9V03X_W]) { uint8 i = 0; for (i = 0; i < MT9V03X_H; i++) { image[i][0] = 0; image[i][1] = 0; image[i][MT9V03X_W - 1] = 0; image[i][MT9V03X_W - 2] = 0; } for (i = 0; i < MT9V03X_W; i++) { image[0][i] = 0; image[1][i] = 0; //image[image_h-1][i] = 0; } } //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- // @函数功能 环岛元素识别处理 // @函数返回 无 //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //全局状态变量 IslandState current_state = NORMAL; uint8_t island_type = 0; // 0:未确定 1:左环岛 2:右环岛 uint8 target_h = 0;//存放断裂点行数 uint16 A_edge = 0; uint16 V_edge = 0; uint8 A_point = 0; uint8 P_point = 0; uint8 V_point = 0; //------------------------------------------------------------------------------------------------------------------ // @函数功能 边界连续性判断 // @参数说明 需要寻找的边线 // @函数返回 有断裂返回0，无断裂返回1 //------------------------------------------------------------------------------------------------------------------ uint8 border_continuous(uint8 *border) { for(uint8 i = MT9V03X_H-1;i > 0;i--) { int8 diff = border[i] - border[i - 1]; if(diff < -4 || diff > 4) { target_h = i; return 0;//有断裂 } } return 1;//无断裂 } //------------------------------------------------------------------------------------------------------------------ // @函数功能 寻找A点 // @函数返回 A点 //------------------------------------------------------------------------------------------------------------------ //左圆环时寻找左边界A点 uint8 find_point_A_l(void) { uint16 j = border_to_edge_l[target_h];//映射 int16 search_min = j - search_range;//遍历点的最小编号 int16 search_max = j + search_range;//遍历点的最大编号 //限定查找区间 if(search_min < 3) { search_min = 3; } if(search_max > data_stastics_l - 2) { search_max = data_stastics_l - 2; } //遍历寻找A点 for(j = search_min;j <= search_max;j++) { if(points_l[j+2][0]<points_l[j][0] && points_l[j+2][1]<points_l[j][1] && points_l[j-2][1] < points_l[j][1]) { A_edge = j; return 1;//找到A点 } } return 0;//未找到A点 } //右圆环时寻找右边界A点 uint8 find_point_A_r(void) { uint16 j = border_to_edge_r[target_h];//映射 int16 search_min = j - search_range;//遍历点的最小编号 int16 search_max = j + search_range;//遍历点的最大编号 //限定查找区间 if(search_min < 3) { search_min = 3; } if(search_max > data_stastics_r - 2) { search_max = data_stastics_r - 2; } //遍历寻找A点 for(j = search_min;j <= search_max;j++) { if(points_l[j+2][0]>points_l[j][0] && points_l[j+2][1]<points_l[j][1] && points_l[j-2][1] < points_l[j][1]) { A_edge = j; return 1;//找到A点 } } return 0;//未找到A点 } //------------------------------------------------------------------------------------------------------------------ // @函数功能 寻找P点 // @函数返回 P点 //------------------------------------------------------------------------------------------------------------------ //左圆环时寻找左边界P点 uint8 find_point_P_l(void) { for(uint8 i = MT9V03X_H - 2;i > 1;i++) { if(l_border[i-2] < l_border[i] && l_border[i+2] < l_border[i]) { P_point = i; return 1;//找到P点 } } return 0;//未找到P点 } //右圆环时寻找左边界P点 uint8 find_point_P_r(void) { for(uint8 i = MT9V03X_H - 2;i > 1;i++) { if(l_border[i-2] > l_border[i] && l_border[i+2] > l_border[i]) { P_point = i; return 1;//找到P点 } } return 0;//未找到P点 } //------------------------------------------------------------------------------------------------------------------ // @函数功能 寻找V点 // @函数返回 V点 //------------------------------------------------------------------------------------------------------------------ //左边V点 uint8 find_point_V_l(void) { uint16 j = border_to_edge_l[target_h];//映射 int16 search_min = j - search_range;//遍历点的最小编号 int16 search_max = j + search_range;//遍历点的最大编号 //限定查找区间 if(search_min < 3) { search_min = 3; } if(search_max > data_stastics_l - 2) { search_max = data_stastics_l - 2; } //遍历寻找V点 for(j = search_min;j <= search_max;j++) { if(points_l[j+2][1]<points_l[j][1] && points_l[j-2][1] < points_l[j][1]) { V_edge = j; return 1;//找到V点 } } return 0;//未找到V点 } //右边V点 uint8 find_point_V_r(void) { uint16 j = border_to_edge_r[target_h];//映射 int16 search_min = j - search_range;//遍历点的最小编号 int16 search_max = j + search_range;//遍历点的最大编号 //限定查找区间 if(search_min < 3) { search_min = 3; } if(search_max > data_stastics_r - 2) { search_max = data_stastics_r - 2; } //遍历寻找V点 for(j = search_min;j <= search_max;j++) { if(points_l[j+2][1]<points_l[j][1] && points_l[j-2][1] < points_l[j][1]) { V_edge = j; return 1;//找到V点 } } return 0;//未找到V点 } //------------------------------------------------------------------------------------------------------------------ // @函数功能 补线 // @参数说明 m补线下方点，n补线上方点，border需要补线的边线数组，end_point需要补到的高度 // @函数返回 无 //------------------------------------------------------------------------------------------------------------------ void patching_line(uint8 m,uint8 n,uint8 *border,uint8 end_point) { float k = (float)( (m - n) / (border[n] - border[m]) ); for(uint8 h = m - 1;h > end_point;h--) { border[h] = (uint8)(border[m] + (m - h) / k); } } //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- // @函数功能 总环岛识别处理函数 // @函数返回 无 //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- void island_handler(void) { switch(current_state) { case NORMAL: //判断初见环岛条件 if(border_continuous(r_border) && !border_continuous(l_border) && find_point_A_l() && find_point_P_l())//判断是否为左环岛 { current_state = SEE_ISLAND; island_type = 1;//左环岛 } if(!border_continuous(r_border) && border_continuous(l_border) && find_point_A_r() && find_point_P_r())//判断是否为右环岛 { current_state = SEE_ISLAND; island_type = 2;//右环岛 } break; case SEE_ISLAND://初见环岛 if(island_type == 1)//左环岛 { //找A，P点 border_continuous(l_border); find_point_A_l(); find_point_P_l(); //补线 A_point = points_l[A_edge][1]; l_border[A_point] = points_l[A_edge][0]; patching_line(A_point,P_point,l_border,P_point); //判断初入环岛条件 if(l_border[MT9V03X_H-1] == border_min && l_border[MT9V03X_H-2] == border_min) { current_state = ENTER_ISLAND; } } if(island_type == 2)//右环岛 { //找A，P点 border_continuous(r_border); find_point_A_r(); find_point_P_r(); //补线 A_point = points_r[A_edge][1]; r_border[A_point] = points_r[A_edge][0]; patching_line(A_point,P_point,r_border,P_point); //判断初入环岛条件 if(r_border[MT9V03X_H-1] == border_max && r_border[MT9V03X_H-2] == border_max) { current_state = ENTER_ISLAND; } } break; case ENTER_ISLAND://初入环岛 if(island_type == 1)//左环岛 { //找P点 find_point_P_l(); //补线 A_point = MT9V03X_H-1; patching_line(A_point,P_point,l_border,P_point); //判断第一次到环岛出口条件 if(!border_continuous(l_border) && border_continuous(r_border) && find_point_V_l()) { current_state = EXIT_ISLAND1; } } if(island_type == 2)//右环岛 { //找P点 find_point_P_r(); //补线 A_point = MT9V03X_H-1; patching_line(A_point,P_point,r_border,P_point); //判断第一次到环岛出口条件 if(border_continuous(l_border) && !border_continuous(r_border) && find_point_V_r()) { current_state = EXIT_ISLAND1; } } break; case EXIT_ISLAND1://第一次到环岛出口 if(island_type == 1)//左环岛 { //找V点 border_continuous(l_border); find_point_V_l(); //补线 V_point = points_l[V_edge][1]; r_border[V_point] = points_l[A_edge][0]; patching_line(119,V_point,r_border,0); //判断即将入环条件 if(!border_continuous(r_border) && find_point_V_r()) { current_state = IN_ISLAND; } } if(island_type == 2)//右环岛 { //找V点 border_continuous(r_border); find_point_V_r(); //补线 V_point = points_r[V_edge][1]; l_border[V_point] = points_r[A_edge][0]; patching_line(119,V_point,l_border,0); //判断即将入环条件 if(!border_continuous(l_border) && find_point_V_l()) { current_state = IN_ISLAND; } } break; case PRE_ENTER://即将入环 if(island_type == 1)//左环岛 { //找V点 border_continuous(r_border); find_point_V_r(); //补线 V_point = points_r[V_edge][1]; r_border[V_point] = points_r[A_edge][0]; patching_line(119,V_point,r_border,0); //判断完全入环条件 if(border_continuous(r_border) && border_continuous(l_border)) { current_state = IN_ISLAND; } } if(island_type == 2)//右环岛 { //找V点 border_continuous(l_border); find_point_V_l(); //补线 V_point = points_l[V_edge][1]; l_border[V_point] = points_l[A_edge][0]; patching_line(119,V_point,l_border,0); //判断完全入环条件 if(border_continuous(r_border) && border_continuous(l_border)) { current_state = IN_ISLAND; } } break; case IN_ISLAND://完全入环 if(island_type == 1)//左环岛 { //条件补线 if(!border_continuous(r_border) && border_continuous(l_border)) { r_border[0] = border_min; patching_line(target_h,0,r_border,0); } //判断第二次到环岛出口条件 if( l_border[MT9V03X_H-1]>border_min && l_border[MT9V03X_H-2]>border_min && r_border[MT9V03X_H-1]==border_max && r_border[MT9V03X_H-1]==border_max) { current_state = EXIT_ISLAND2; } } if(island_type == 2)//右环岛 { //条件补线 if(!border_continuous(l_border) && border_continuous(r_border)) { l_border[0] = border_max; patching_line(target_h,0,l_border,0); } //判断第二次到环岛出口条件 if( l_border[MT9V03X_H-1]==border_min && l_border[MT9V03X_H-2]==border_min && r_border[MT9V03X_H-1]<border_max && r_border[MT9V03X_H-1]<border_max) { current_state = EXIT_ISLAND2; } } break; case EXIT_ISLAND2://第二次到环岛出口 if(island_type == 1)//左环岛 { //判断最终出环条件 if(!border_continuous(l_border) && border_continuous(r_border)) { current_state = FINAL_EXIT; } } if(island_type == 2)//右环岛 { //判断最终出环条件 if(border_continuous(l_border) && !border_continuous(r_border)) { current_state = FINAL_EXIT; } } break; case FINAL_EXIT://最终出环 if(island_type == 1)//左环岛 { //补线 border_continuous(l_border); patching_line(119,target_h,l_border,target_h); //结束条件 if(border_continuous(l_border) && border_continuous(r_border)) { current_state = NORMAL; island_type = 0; } } if(island_type == 2)//右环岛 { //补线 border_continuous(r_border); patching_line(119,target_h,r_border,target_h); //结束条件 if(border_continuous(l_border) && border_continuous(r_border)) { current_state = NORMAL; island_type = 0; } } break; } } //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- // @函数功能 获取车身偏差 // @函数返回 车身偏差error //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- int16 error = 1000; //误差100 int16 error_last = 0; //上次误差 void car_error(void) { uint8 i = 0; int32 num = 0; //int16 num = 0 for(i = 1;i < MT9V03X_H;i++) { num += (center_line[i] - (MT9V03X_W / 2)); } error_last = error; error = num; } //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- // @函数功能 最终处理函数 // @函数返回 无 //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- //----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- uint8 change = 0; uint8 change_last = 0; void image_process(void) { uint16 i; uint8 hightest = 0;//定义一个最高行，tip：这里的最高指的是y值的最小 Get_image(mt9v03x_image);//获得一副灰度图像 turn_to_bin();//大津法二值化。 //提取赛道边界 image_filter(bin_image);//滤波减少噪声 image_draw_rectan(bin_image);//给图像画黑框为八领域做准备 //清零 data_stastics_l = 0; data_stastics_r = 0; if (get_start_point(MT9V03X_H - 2))//找到起点了，再执行八领域，没找到就一直找 { navigation_flag = 0; //判断直角弯 uint8 m = 0,n = 0, j = 0; for(j = 1;j < MT9V03X_W;j++) { if(bin_image[60][j] == 255) { break; } if(bin_image[62][j] == 255) { break; } } if(j == MT9V03X_W) { for(j = 119;j > 55;j--) { if(bin_image[j][5] == 255 && bin_image[j][7] == 255) { m = 1; } if(bin_image[j][115] == 255 && bin_image[j][113] == 255) { n = 1; } } } if(m == 1 && n == 0) { navigation_flag = 1; } if(m == 0 && n == 1) { navigation_flag = 2; } //八领域处理 search_l_r((uint16)USE_num, bin_image, &data_stastics_l, &data_stastics_r, start_point_l[0], start_point_l[1], start_point_r[0], start_point_r[1], &hightest); // 从爬取的边界线内提取边线 ， 这个才是最终有用的边线 get_left(data_stastics_l); get_right(data_stastics_r); //处理函数 island_handler();//环岛元素识别处理 } else { navigation_flag = 3; } for (i = hightest; i < MT9V03X_H-1; i++) { center_line[i] = (l_border[i] + r_border[i]) >> 1;//求中线 } if(bin_image[118][8] == 0 && bin_image[118][40] == 255 && bin_image[118][100] == 255 && bin_image[118][148] == 255 && bin_image[118][180] == 0 && bin_image[118][94] == 255) { change_last = change; change = 1; } else { change = 0; } if(change == 1 && change_last == 0) { stop++; } 以上代码是否可通过调节参数来减少曝光问题，如若可以该调节哪个部分或需添加什么代码