Crop image OpenCV

Open Source Computer Vision (OpenCV) is an open-sourceA software or a library whose code is made available to the public. computer vision and machine learning software library which provides a wide range of functions and algorithms to process and analyze images and videos.

Note: You can learn more about OpenCV.

Image matrix

An image is typically represented as a two-dimensional matrix, where each element corresponds to a pixel value within the image. These pixel values store information regarding the color intensity of each pixel.

In the case of grayscale images, each pixel value ranges from $0 \textnormal{ to } 255$. For example, a greyscaled image of size $4 \times 3$ pixels will be:

However, for colored images, each pixel value is represented by an RGB (Red, Green, Blue) matrix in the form [R, G, B]. The R, G, and B values individually range from $0 \textnormal{ to } 255$, indicating the intensity of the respective color channels. For example, a colored image of dimensions $2 \times 2 \times 3$ pixels might have an image matrix like the following:

Cropping an image

Cropping an image means selecting and extracting a specific rectangular region from the original image. Python library OpenCV can do this job efficiently as follows:

Note: You can drag the image windows to have a better comparison.

Code explanation

• Line 1: Imports cv2 library.

• Line 4: Loads the image (named image.jpg) that's supposed to be cropped and stores it in original_image. This image has the dimensions of $700 \times 700$ pixels.

• Lines 7–8: output_width and output_height store the dimensions of the resultant cropped image.

• Lines 11–12: start_x stores the starting x-coordinate of the point from where the image will be cropped. start_y does the same thing for y-coordinate.

• Line 15: Slices the original image matrix (original_image) and stores it in cropped_image. Now, the cropped_image variable contains the image matrix of the cropped image.

• Line 18: Displays the uncropped image.

• Line 19: Displays the cropped image.

• Line 20: waitKey() method waits for the user to press any key to close all the windows.

• Line 21: Closes all the opened windows at the end of the program.

• and storing it in original_image variable.

Learn more about it:

• How to blur images using OpenCV.

• How to stitch two images using OpenCV.

• How to dilate images using OpenCV.