Color segmentation

Overview

Color segmentation is the process by which specific target parts of the image are extracted based on , in this case , their color.

Example

Using the below image, extract the vehicle color. We will display both a segmented image and a monochromatic image(which will exclude the vehicle from the monochrome color scale).

For this, we import ColorDetect as below:

>>> import cv2
>>> from colordetect import ColorDetect
>>> my_car = ColorDetect('car.jpg')
>>> monochromatic, gray, segmented, mask = my_car.get_segmented_image(lower_bound=(0, 70, 0), upper_bound=(80, 255, 255))
>>> cv2.imshow('Segmented', segmented)
>>> cv2.imshow('monochromatic', monochromatic)
>>> cv2.wait(0)

The lower and upper bounds act as a range of colors from which to look from. as a result, our segmented image would appear as below:

get_segmented_image() accepts more parameters such as erode_iterations,dilate_iterations, use_grab_cut, which is set True by default and gc_iterations . You may increase or decrease these values depending on the clarity needed off the image.

Our monochromatic image: