Image Border Detection and Cropping

This Python script is designed to detect and crop the borders of images stored in a specified folder. It can be useful for removing unwanted white or blank margins from scanned documents or images.

Prerequisites

Before using this script, you need to have the following dependencies installed:

• OpenCV (cv2):

pip install opencv-python

Usage

1. Clone or download this repository to your local machine.

2. Place the images you want to process in a folder of your choice. You can set the input folder by modifying the input_folder variable in the script.

3. Optionally, specify the output folder where the cropped images will be saved by modifying the output_folder variable in the script. If not provided, it defaults to a folder with the same name as the input folder but prefixed with "cropped_".

4. Optionally, you can set target dimensions for the cropped images by modifying the target_width and target_height variables. If you want to keep the original dimensions, set these variables to None.

5. Run the script:

python remove_black_borders.py

• The script will now process all the supported files in the input folder, detect and crop borders from all sides, and save the cropped images in the output folder.

Customization

• The white_threshold parameter in the BorderAnalyzer class has been set to 85 to enhance the detection of borders, offering improved separation between the actual content and the surrounding borders, even in images with intricate patterns or not very light details.
• In image processing, pixel values typically range from 0 to 255, where 0 represents black and 255 represents white. The white_threshold parameter is used to determine how light a pixel must be to be considered part of a white border. For example, white_threshold value closer to 255 would make the script more sensitive to white and very light colours.

Example

In the provided script, the default input_folder is set to "book," and the default output_folder is set to "cropped_book." You can replace these values with your own folder paths.

input_folder = "your_input_folder"
output_folder = "your_output_folder"

Please replace "your_input_folder" and "your_output_folder" with the actual folder paths you want to use.

License

This script is licensed under the MIT License.