💡[Feature]: Image segmentation using thresholding techniques

[Suvadip-sana]

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Feature Description

This program is for image segmentation using thresholding techniques. It includes two types of thresholding methods: basic global thresholding and Otsu's thresholding. Here’s a breakdown of each section:

Basic Global Thresholding:

The function basic_global_thresholding calculates a global threshold by iteratively finding the mean of foreground and background pixel values. It stops when the difference between the current mean and the previous mean falls below a specified threshold (delthreshold).
Otsu's Thresholding:

The otsu_thresholding function implements Otsu's method, which calculates a threshold that minimizes the intra-class variance (variance within foreground and background regions). This threshold is more effective for bimodal images (images with a clear foreground and background).

Use Case

Image Segmentation:

The function segmented_image applies the calculated threshold (either global or Otsu's) to segment the image into binary values (0 and 1), creating a clear distinction between foreground and background regions.
Visualization:

The program reads a grayscale image, displays the original image, calculates the optimal threshold using Otsu’s method, segments the image based on this threshold, and then displays the segmented (thresholded) image.

Benefits

@sanjay-kv Sir please assign me this. I want to add this under Open CV project.

Add ScreenShots

Priority

High

Record

• I have read the Contributing Guidelines
• I'm a GSSOC'24 contributor
• I want to work on this issue

[github-actions]

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[sanjay-kv]

please see pinned issue

[github-actions]

Hello @Suvadip-sana! Your issue #1576 has been closed. Thank you for your contribution!