Work

Novel color space representation extracted by NMF to segment a color image

Year: 2024

Type: article

Abstract: This paper considers the task of separating pixels in color image into background and foreground classes. Using the machine learning technique known as Nonnegative Matrix Factorization, data pertaining to different color channels – selected by color spaces – are combined, and a novel space representation is extracted. The novel representation of the image includes additional information, namely “metacolor”, which could be related to foreground and background and adopted to improve binary segmentation of the investigated image. In both qualitative and quantitative experiments, the use of novel color space representation produces some improvements in the binary segmentation results when it compared to those obtained applying common simpler thresholding algorithms directly to the original image.

Source: Journal of Computational Mathematics and Data Science

DOI: 10.1016/j.jcmds.2024.100104

Authors: Ciro Castiello, Nicoletta Del Buono, Flavia Esposito

Institution: University of Bari Aldo Moro

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,000

OpenAlex ID: W4403548144

FWCI: 1.007

Cites: 28

Cited by: 7

Related to: 10