A Robust Rapid Approach to Image Segmentation with Optimal Thresholding and Watershed Transform

TL;DR

This paper introduces a fast, robust image segmentation method combining watershed transform with auxiliary techniques like gradient masking and dilation, adaptable to various image types for improved efficiency.

Contribution

It presents a novel, efficient segmentation algorithm that integrates watershed transform with auxiliary schemes, enhancing robustness and adaptability across diverse images.

Findings

Operates quickly with high robustness

Effective segmentation across different image types

Improves upon existing watershed-based methods

Abstract

This paper describes a novel method for partitioning image into meaningful segments. The proposed method employs watershed transform, a well-known image segmentation technique. Along with that, it uses various auxiliary schemes such as Binary Gradient Masking, dilation which segment the image in proper way. The algorithm proposed in this paper considers all these methods in effective way and takes little time. It is organized in such a manner so that it operates on input image adaptively. Its robustness and efficiency makes it more convenient and suitable for all types of images.