Day #150- Gabor filter

What is Gabor filter ?

• Linear filter used for texture analysis
• Gabor filter allow a certain band of frequency and reject the others

What are its Significance ?

• Edges and texture changes captured
• Filters are convolved with signal and Gabor space is obtained
• 2D Gabor filter is Gaussian Kernel modulated by a sinusoidal plane wave in spatial domain

Example Code ?

	import numpy as np
	import cv2
	#cv2.getGaborKernet(ksize,sigma,theta,lambda,gamma,psi,ktype)
	#size of habor filter
	#sigma - standard deviation from gaussian
	#theta - orientation from normal to the parallel stripes
	#gamma - spacial aspect ratio
	#psi - phase offset
	#ktype - type and range values for each pixel in gabor kernel It can be CV_32F or CV_64F
	def CheckGaborfilter(gabor_kernel):
	inputimage = cv2.imread(r'D:\OpenCVExamples\IMG_20180923_150233_282.jpg')
	grayimage = cv2.cvtColor(inputimage,cv2.COLOR_BGR2GRAY)
	filteredimage = cv2.filter2D(grayimage,cv2.CV_8UC3,gabor_kernel)
	cv2.imshow('Original Image',inputimage)
	cv2.imshow('Filtered Image',filteredimage)
	cv2.waitKey(0)
	return
	#ksize, sigma, theta, lambd, gamma[, psi[, ktype]]
	#Example 1
	gabor_kernel = cv2.getGaborKernel((21,21),8.0,np.pi/4,10.0,0.5,0,ktype=cv2.CV_32F)
	CheckGaborfilter(gabor_kernel)
	#Example 2
	gabor_kernel = cv2.getGaborKernel((10,10),5.0,np.pi/4,10.0,0.5,1,ktype=cv2.CV_64F)
	CheckGaborfilter(gabor_kernel)
	#Example 3
	gabor_kernel = cv2.getGaborKernel((21,21),8.0,np.pi/4,5.0,0.5,0,ktype=cv2.CV_64F)
	CheckGaborfilter(gabor_kernel)
	#Example 4
	gabor_kernel = cv2.getGaborKernel((21,21),8.0,np.pi/4,10.0,0.5,0,ktype=cv2.CV_64F)
	CheckGaborfilter(gabor_kernel)
	cv2.destroyAllWindows()

view raw gaborfilter.py hosted with ❤ by GitHub

This also can be applied for feature extraction from images.

Ref - Link1 , Link2

Happy Learning!!!