python.zip_python gabor_python gabor特征_vaporu6x_特征提取_特征提取 python

#!/usr/bin/python # -*- coding: UTF-8 -*- import cv2 import numpy as np import pylab as pl from skimage import data img = data.camera() def build_filters(): filters = [] ksize = [7, 9, 11, 13, 15, 17] # gabor尺度，6个 lamda = np.pi / 2.0 # 波长 for theta in np.arange(0, np.pi, np.pi / 4): # gabor方向，0°，45°，90°，135°，共四个 for K in xrange(6): kern = cv2.getGaborKernel((ksize[K], ksize[K]), 1.0, theta, lamda, 0.5, 0, ktype=cv2.CV_32F) kern /= 1.5 * kern.sum() filters.append(kern) return filters ### Gabor滤波过程 def process(img, filters): accum = np.zeros_like(img) # accum = cv2.filter2D(img, cv2.CV_8UC3, filters) for kern in filters: fimg = cv2.filter2D(img, cv2.CV_8UC3, kern) #cv2.filter2D()允许用户使用自定义过滤器卷积图像 np.maximum(accum, fimg, accum) return accum ### Gabor特征提取 def getGabor(img, filters): res = [] #滤波结果 for i in xrange(len(filters)): res1 = process(img, filters[i]) res.append(np.asarray(res1)) pl.figure(2) for temp in xrange(len(res)): pl.subplot(4, 6, temp+1) pl.imshow(res[temp], cmap='gray') pl.show() return res #返回滤波结果,结果为24幅图，按照gabor角度排列 print getGabor(img, build_filters())