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I understand the concept of the gabor kernel and how it can be used to identify directional edges. So I want to use it to identify barcode lines in images.

However when I filter an image with a gabor kernel I always get a blank/black result. Can you provide feedback on what I need to do to get Gabor to identify the vertical lines in an image, ie, produce a result that has white where the vertical edges are?

Input image:

Result:

import cv2
import numpy as np  

def deginrad(degree):
    radiant = 2*np.pi/360 * degree
    return radiant

def main():
    src = cv2.imread('./images/barcode1.jpg', cv2.IMREAD_GRAYSCALE)

    # Introduce consistency in width
    const_width = 300
    aspect = float(src.shape[0]) / float(src.shape[1])
    src = cv2.resize(src, (const_width, int(const_width * aspect)))

    src = cv2.GaussianBlur(src, (7,7), 0)

    # Apply gabor kernel to identify vertical edges
    g_kernel = cv2.getGaborKernel((9,9), 8, deginrad(0), 5, 0.5, 0, ktype=cv2.CV_32F)
    gabor = cv2.filter2D(src, cv2.CV_8UC3, g_kernel)

    # Visual the gabor kernel
    h, w = g_kernel.shape[:2]
    g_kernel = cv2.resize(g_kernel, (20*w, 20*h), interpolation=cv2.INTER_CUBIC)

    cv2.imshow('src', src)
    cv2.imshow('gabor', gabor)  # gabor is just black
    cv2.imshow('gabor kernel', g_kernel)
    cv2.waitKey(0)

if __name__ == "__main__":
    main()