在彩色图像上画一条直线：

   for item in lc_imglists:img_ori = cv2.imread(item)cv2.line(img_ori,(100,100),(1000,1000),(0,0,255),3)imshow(img_ori,600,600,'img',True)

如果对原图像上下，或左右翻转后再画直线，第一想法是：

    for item in lc_imglists:img = cv2.imread(item)[:,0:2000,:]img = np.flipud(img)  # np.fliplrcv2.line(img,(100,100),(1000,1000),(0,0,255),3)imshow(img,600,600,'img',True)

图像中没有显示所画的红线，退而求其次，对每个通道进行翻转，再进行拼接：

    for item in lc_imglists:img = cv2.imread(item)[:,0:2000,:]flag = Trueif flag:b,g,r = cv2.split(img)b = np.fliplr(b)g = np.fliplr(g)r = np.fliplr(r)img[:,:,0] = bimg[:,:,1] = gimg[:,:,2] = rcv2.line(img,(100,100),(1000,1000),(0,0,255),3)imshow(img,600,600,'img',True)

水平 竖直投影法在图像分割中应用广泛, 代码实现如下:

def CalcImgProjection(img):rowProjection = np.mean(img, axis=0)colProjection = np.mean(img, axis=1)plt.figure()plt.subplot(121)plt.imshow(img, 'gray')plt.title('img')plt.subplot(222)plt.plot(rowProjection, 'r*')plt.title('row')plt.subplot(224)plt.plot(colProjection, 'go')plt.title('col')plt.show()if __name__ == '__main__':data = './datasets/lowcontrast_thread/'type = '*.bmp'imglists = glob.glob(data + type)for item in imglists:img = cv2.imread(item,0)[:,:2500]CalcImgProjection(img)

利用像素值的变化关系,选择合理的阈值,即可实现目标区域的分割.