Add gabor filter

digital_image_processing/filters/gabor_filter.py

@@ -0,0 +1,85 @@
+# Implementation of the Gaborfilter
+# https://en.wikipedia.org/wiki/Gabor_filter
+import numpy as np
+from cv2 import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filter2D, imread, imshow, waitKey
+
+
+def gabor_filter_kernel(
+ ksize: int, sigma: int, theta: int, lambd: int, gamma: int, psi: int
+) -> np.ndarray:
+ """
+ :param ksize: The kernelsize of the convolutional filter (ksize x ksize)
+ :param sigma: standard deviation of the gaussian bell curve
+ :param theta: The orientation of the normal to the parallel stripes
+ of Gabor function.
+ :param lambd: Wavelength of the sinusoidal component.
+ :param gamma: The spatial aspect ratio and specifies the ellipticity
+ of the support of Gabor function.
+ :param psi: The phase offset of the sinusoidal function.
+
+ >>> gabor_filter_kernel(3, 8, 0, 10, 0, 0).tolist()
+ [[0.8027212023735046, 1.0, 0.8027212023735046], [0.8027212023735046, 1.0, \
+0.8027212023735046], [0.8027212023735046, 1.0, 0.8027212023735046]]
+
+ """
+
+ # prepare kernel
+ # the kernel size have to be odd
+ if (ksize % 2) == 0:
+ ksize = ksize + 1
+ gabor = np.zeros((ksize, ksize), dtype=np.float32)
+
+ # each value
+ for y in range(ksize):
+ for x in range(ksize):
+ # distance from center
+ px = x - ksize // 2
+ py = y - ksize // 2
+
+ # degree to radiant
+ _theta = theta / 180 * np.pi
+ cos_theta = np.cos(_theta)
+ sin_theta = np.sin(_theta)
+
+ # get kernel x
+ _x = cos_theta * px + sin_theta * py
+
+ # get kernel y
+ _y = -sin_theta * px + cos_theta * py
+
+ # fill kernel
+ gabor[y, x] = np.exp(
+ -(_x ** 2 + gamma ** 2 * _y ** 2) / (2 * sigma ** 2)
+ ) * np.cos(2 * np.pi * _x / lambd + psi)
+
+ return gabor
+
+
+if __name__ == "__main__":
+ import doctest
+
+ doctest.testmod()
+ # read original image
+ img = imread("../image_data/lena.jpg")
+ # turn image in gray scale value
+ gray = cvtColor(img, COLOR_BGR2GRAY)
+
+ # Apply multiple Kernel to detect edges
+ out = np.zeros(gray.shape[:2])
+ for theta in [0, 30, 60, 90, 120, 150]:
+ """
+ ksize = 10
+ sigma = 8
+ lambd = 10
+ gamma = 0
+ psi = 0
+ """
+ kernel_10 = gabor_filter_kernel(10, 8, theta, 10, 0, 0)
+ out += filter2D(gray, CV_8UC3, kernel_10)
+ out = out / out.max() * 255
+ out = out.astype(np.uint8)
+
+ imshow("Original", gray)
+ imshow("Gabor filter with 20x20 mask and 6 directions", out)
+
+ waitKey(0)