Comparing the Performance of L*A*B* and HSV Color Spaces with Respect to Color Image Segmentation

TL;DR

This paper compares LAB and HSV color spaces for image segmentation, finding HSV generally performs better based on mse and psnr metrics, highlighting the importance of color space choice.

Contribution

It provides a comparative analysis of LAB and HSV color spaces specifically for color image segmentation, which is less explored in existing literature.

Findings

HSV outperforms LAB in segmentation quality

Performance measured using mse and psnr metrics

HSV's superiority suggests its preference for segmentation tasks

Abstract

Color image segmentation is a very emerging topic for image processing research. Since it has the ability to present the result in a way that is much more close to the human yes perceive, so todays more research is going on this area. Choosing a proper color space is a very important issue for color image segmentation process. Generally LAB and HSV are the two frequently chosen color spaces. In this paper a comparative analysis is performed between these two color spaces with respect to color image segmentation. For measuring their performance, we consider the parameters: mse and psnr . It is found that HSV color space is performing better than LAB.