opencv3+python3.5成语填字游戏（一）印刷体汉字的

• 首先这是一个成语填字游戏，大概就是一张成语填字游戏图片，通过opencv图像识别后转为矩阵，再通过解算法，解出答案，在显示到图片上。

GitHub源代码

image

本文采用投影分割法对印刷体汉字进行分割。

投影分割是先水平方向投影，在竖直方向投影，或者先竖直方向再水平方向投影。本文选用先竖直，再水平。

• 竖直投影。

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代码：

<pre name="code" class="python" style="box-sizing: border-box; margin: 0px 0px 24px; padding: 0px 16px; overflow-x: auto; background-color: rgb(240, 240, 240); font-family: Consolas, Inconsolata, Courier, monospace; font-size: 12px; line-height: 20px; color: rgb(0, 0, 0); font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: 2; text-align: justify; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px;">#针对的是印刷版的汉字，所以采用了投影法分割
#此函数是行分割，结果是一行文字
def YShadow(path):
    img  = cv2.imread(path)   #原图像
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #灰度图像
    height,width = img.shape[:2]

    #blur = cv2.GaussianBlur(gray,(5,5),0) #高斯模糊

    blur = cv2.blur(gray,(8,8)) #均值模糊
    thresh = cv2.adaptiveThreshold(blur,255,1,1,11,2)  #自适应阈值分割
    temp = thresh

    if(width > 500 and height > 400): #图像字体较小时，需要进行膨胀操作
        kernel = np.ones((5,5),np.uint8) #卷积核
        dilation = cv2.dilate(thresh,kernel,iterations = 1) #膨胀操作使得单个文字图像被黑像素填充
        temp = dilation

    '''
    cv2.imshow('image',temp)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    '''

    perPixelValue = 1 #每个像素的值
    projectValArry = np.zeros(width, np.int8) #创建一个用于储存每列黑色像素个数的数组

    for i in range(0,height):
        for j in range(0,width):
            perPixelValue = temp[i,j]
            if (perPixelValue == 255): #如果是黑字，对应位置的值+1
                projectValArry[i] += 1
       # print(projectValArry[i])

    canvas = np.zeros((height,width), dtype="uint8")

    for i in range(0,height):
        for j in range(0,width):
            perPixelValue = 255 #白色背景
            canvas[i, j] = perPixelValue

    for i in range(0,height):
        for j in range(0,projectValArry[i]):
            perPixelValue = 0 #黑色直方图投影
            canvas[i, width-j-1] = perPixelValue
    '''
    cv2.imshow('canvas',canvas)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    '''

    list = []
    startIndex = 0 #记录进入字符区的索引  
    endIndex = 0 #记录进入空白区域的索引  
    inBlock = 0 #是否遍历到了字符区内  

    for i in range(height):
        if (inBlock == 0 and projectValArry[i] != 0): #进入字符区
            inBlock = 1  
            startIndex = i
        elif (inBlock == 1 and projectValArry[i] == 0):#进入空白区
            endIndex = i
            inBlock = 0
            subImg = gray[startIndex:endIndex+1,0:width] #将对应字的图片截取下来
            #print(startIndex,endIndex+1)
            list.append(subImg)#添加这个字图像到list
    #print(len(list))
    return list</pre>

• 水平投影

#对行字进行单个字的分割
def XShadow(path):
    img  = cv2.imread(path)       
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    height,width = img.shape[:2]
   # print(height,width)
    #blur = cv2.GaussianBlur(gray,(5,5),0)

    blur = cv2.blur(gray,(8,8))
    thresh = cv2.adaptiveThreshold(blur,255,1,1,11,2) 

    if(width > 500):
        kernel = np.ones((4, 4),np.uint8) #卷积核
    else:
        kernel = np.ones((2, 2),np.uint8) #卷积核
    dilation = cv2.dilate(thresh,kernel,iterations = 1) #膨胀操作使得单个文字图像被黑像素填充

    '''
    cv2.imshow('image',thresh)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    '''

    perPixelValue = 1 #每个像素的值
    projectValArry = np.zeros(width, np.int8) #创建一个用于储存每列黑色像素个数的数组

    for i in range(0,width):
        for j in range(0,height):
            perPixelValue = dilation[j,i]
            if (perPixelValue == 255): #如果是黑字
                projectValArry[i] += 1
       # print(projectValArry[i])

    canvas = np.zeros((height,width), dtype="uint8")

    for i in range(0,width):
        for j in range(0,height):
            perPixelValue = 255 #白色背景
            canvas[j, i] = perPixelValue

    for i in range(0,width):
        for j in range(0,projectValArry[i]):
            perPixelValue = 0 #黑色直方图投影
            canvas[height-j-1, i] = perPixelValue
    '''
    cv2.imshow('canvas',canvas)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    '''

    list = []
    startIndex = 0 #记录进入字符区的索引  
    endIndex = 0 #记录进入空白区域的索引  
    inBlock = 0 #是否遍历到了字符区内  

    for i in range(width):
        if (inBlock == 0 and projectValArry[i] != 0): #进入字符区
            inBlock = 1  
            startIndex = i
        elif (inBlock == 1 and projectValArry[i] == 0): #进入投影区
            endIndex = i
            inBlock = 0
            #subImg = gray[0:height, startIndex:endIndex+1] #endIndex+1
            #print(startIndex,endIndex+1)
            list.append([startIndex, 0, endIndex-startIndex-1, height])
    #print(len(list))
    return list</pre>

分割完后，将对应图片样本存储到对应文件夹，每个字共10种样本

将这些样本及标记保存后，分别加载到samples.npy, label.npy中。供后续的机器学习算法训练使用。

下篇讲解填字图片汉字的提取与机器学习算法训练样本，识别汉字的过程。