Publication Type:

Conference Paper

Source:

Smart Computing Paradigms: New Progresses and Challenges, Springer Singapore, Singapore (2020)

ISBN:

9789811396830

Abstract:

Images have been widely used in today's life varying from personal usage with Flickr, Facebook to the analysis of hyperspectral images. Availability of such huge volume of images in digital form requires an automatic analysis on visual content. The major challenge in content labeling is in segmentation, which divides the image into regions. Our work focuses on the segmentation technique that adapts based on regions in the natural images. The proposed method used automatic seed selection by analyzing the dynamic color distribution of the image. The experimental results on datasets show the better performance of our method.

Cite this Research Publication

R. Aarthi and Shanmuga Priya S., “Automated Histogram-Based Seed Selection for the Segmentation of Natural Scene”, in Smart Computing Paradigms: New Progresses and Challenges, Singapore, 2020.