OpenCV图像处理基础（一）

图像处理基础，等大小图片相似度匹配

基于RGB通道的像素点相似度匹配算法思路

def compare_by_RGB(image_1,image_2):
    """
    基于通道和的差  
    :param image_1:  
    :param image_2:
    :return:
    """
    G_1 = 0
    B_1 = 0
    R_1 = 0
    G_2 = 0
    B_2 = 0
    R_2 = 0
    #第一个图像矩阵通道和
    for x in image_1:
        for y in x:
            G_1 += y[0]
            B_1 += y[1]
            R_1 += y[2]
    #第二个图像矩阵通道和
    for x in image_2:
        for y in x:
            G_2 += y[0]
            B_2 += y[1]
            R_2 += y[2]
    #图像矩阵各通道相似度
    inc_G = 1 - math.fabs(G_1 - G_2) / G_2
    inc_B = 1 - math.fabs(B_1 - B_2) / B_2
    inc_R = 1 - math.fabs(R_1 - R_2) / R_2
    dec = (inc_G + inc_B + inc_R) / 3
    return dec

根据不相似的像素点统计

def compare_by_pixe(pic1, pic2):
    """
    方法二，基于像素点相似数量统计
    :param pic1:
    :param pic2:
    :return:totlepix 像素点个数,diffcount 相似度 ,nptg,ptg
    """
    res={}
    #获取行数列数和通道数
    sp1 = pic1.shape
    sp2 = pic2.shape
    #获取矩阵大小
    res['totlepix'] = pic1.size # pix*3 矩阵大小等于像素点数乘以3
    #判断两张图片的行列数是否相同
    if sp1 != sp2:
        ret = "The two picture is in Different range"
        return ret
    DiffCount = 0
    #遍历矩阵行和列
    for index1 in range(sp1[0]):
        for index2 in range(sp1[1]):
            (b1, g1, r1) = pic1[index1, index2]
            (b2, g2, r2) = pic2[index1, index2]
            if (b1, g1, r1) != (b2, g2, r2):
                DiffCount = DiffCount + 1
    res['totlepix'] = res['totlepix'] / 3
    #相似度=不同的像素点数/像素点总数
    res['diffcount'] =1- DiffCount/ res['totlepix']
    return res

主函数测试

if __name__=="__main__":
    #相似度阈值  
    threshold_value=0.75
    path="./lab1_data/lab1_video.mp4"
    cap=cv2.VideoCapture(path)
    count=0
    if cap.isOpened():
        #锁，用来判断是否为第一帧
        flag=False
        while 1:
            ret,frame=cap.read()
            #缩小图片
            image=cv2.resize(frame,(32,32),interpolation=cv2.INTER_CUBIC)
            if flag==True:
                res=compare_by_pixe(image, temp)
                if res["diffcount"]<threshold_value:
                    cv2.imwrite("./lab1_save_data/"+str(count)+".jpg",frame)
                    count += 1
                #记录当前帧
                temp=image
            if flag==False:
                flag=True
                temp=image
            cv2.imshow("image",frame)
            if cv2.waitKey(10)=='q':
                break
        cv2.destroyAllWindows()