Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/2548 2018 2018 Technical Engineering College /Northren Technical University, Mosul, Iraq Marwa Marwa Technical Engineering College /Northren Technical University, Mosul, Iraq Ahmed S. Ibrahim Al .. Department of Computer Science /Collage of Computer Science and Mathematics / University of Mosul, Iraq Mohammad Abid Al Al-Hashim Accurate classification of malignant and benign skin lesions is crucial in dermatology. In this novel research, we propose robust image analysis methodology for skin lesion classification that integrates color-based segmentation with luminosity analysis. Our approach is evaluated on a dataset of 400 skin images, with equal representation of malignant and benign samples. By computing mean color values for the Red Channel Color (RCC), Green Channel Color (GCC), and Blue Channel Color (BCC) in groups of 10 samples, we establish a classification range for precise diagnosis, this research introduces a novel dimension by harnessing the potential of the CIE Lab Color characteristics for skin lesion detection as the most reliable scale for distinguishing between benign and malignant samples. The smaller and more thought variety ranges saw in the glow examination improve difference and perceivability, consequently working with prevalent sore separation. By featuring the meaning of mean histograms for each variety channel, this complete exploration adds to propelling the area of dermatology and presents an imaginative methodology that holds guarantee for PC helped conclusion frameworks in skin malignant growth discovery. 2024 2024 88 97 10.54216/FPA.150108 https://www.americaspg.com/articleinfo/3/show/2548