• P. Lekhya Naga Bhavani
• Dr.CH.Santhi Rani
• L Chaitanya Koushik
• Ch Bhaskar Gopi Chand

In computer vision tasks involving colour images, it is imperative to classify pixels based on their colour and segment the corresponding sections. The main challenges in developing methods for precisely classifying pixels in accordance with colour are the variations in digital representation, linguistic theory, and human colour perception. With a novel mechanism that combines mathematical analysis, colour wheel, fuzzy colour triangle, and multiple label group, our solution seeks to address these problems. This method yields accurate descriptions of all detected colours and allows pixels to be automatically classified into 12 standard colour categories. Based on colour theory and statistics, the method provides a trustworthy, unsupervised, and impartial method of choosing colours. The proposed "Reduced-ABSCCA (AB Space for colour Classification and Analysis)” model was evaluated by conducting the several experiments. It provides 98% of accurate colour naming and segmentation and can be support several computer vision tasks.

Colour image analysis, colour models, colour image segmentation, pixel classification, fuzzy colour theory.

"A NOVEL METHOD FOR COMPUTER VISION TASK AND COLOUR ANALYSIS FOR MULTI-LABEL PIXEL CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d203-d211, April-2024, Available :http://www.jetir.org/papers/JETIR2404331.pdf

"A NOVEL METHOD FOR COMPUTER VISION TASK AND COLOUR ANALYSIS FOR MULTI-LABEL PIXEL CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd203-d211, April-2024, Available at : http://www.jetir.org/papers/JETIR2404331.pdf