指纹图像增强源码.rar

import matplotlib.pyplot as plt import numpy as np #计算灰度直方图 def calcGrayHist(image): h,w = image.shape grayHist = np.zeros([256],np.int8) for r in range(h): for c in range(w): #0-255 => 1-256 统计所有的灰度值 grayHist[image[r,c]] += 1 return grayHist def plot_hist(image): grayHist = calcGrayHist(image) x_range = range(256) plt.plot(x_range, grayHist, 'r', linewidth=2, c='black') y_maxValue = np.max(grayHist) plt.axis([0, 255, 0, y_maxValue]) # 设置坐标轴标签 plt.xlabel('gray Level') plt.ylabel('number of pixels') # 显示直方图 plt.show() #边缘断裂连接 def connect(image): h,w = image.shape for i in range(2,h-2): for j in range(2,w-2): #如果中心点位置为255 考虑八邻域 if image[i,j] == 255: num = 0 for k in range(-1,2): for l in range(-1,2): if k != 0 or l != 0 and image[i+k,i+l] == 255: num += 1 #如果八邻域中只有一个点是255，说明该中心点为端点，则考虑其他领域 if num == 1: for k in range(-2,3): for l in range(-2,3): #非八邻域 if not(k<2 and k>-2 and l<2 and l>-2) and image[i+k,i+l] == 255: image[i+k,i+l] = 255 return image