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The objectives of the proposed work are twofold. Firstly, to develop a specialized light weight CRPU-Net for the segmentation of polyps in colonoscopy images. Secondly, to conduct a comparative analysis of the performance of CRPU-Net with implemented state-of-the-art models. We have utilized two distinct colonoscopy image datasets such as CVC-ColonDB and CVC-ClinicDB. This paper introduces the CRPU-Net, a novel approach for the automated segmentation of polyps in colorectal regions. A comprehensive series of experiments was conducted using the CRPU-Net, and its performance was compared with that of state-of-the-art models such as VGG16, VGG19, U-Net and ResUnet++. Additional analysis such as ablation study, generalizability test and 5-fold cross validation were performed. The CRPU-Net achieved the segmentation accuracy of 96.42% compared to state-of-the …