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Monaural speech separation is the process of separating the target speech from the noisy speech mixture recorded using single microphone. It is a challenging problem in speech signal processing, and recently, computational auditory scene analysis (CASA) finds a reasonable solution to solve this problem. This research work proposes an image analysis-based algorithm to enhance the binary T–F mask obtained in the initial segmentation stage of CASA-based monaural speech separation systems to improve the speech quality. The proposed algorithm consists of labeling the initial segmentation mask, boundary extraction, active pixel detection and finally eliminating the noisy non-active pixels. In labeling, the T–F mask obtained from the initial segmentation is labeled as periodicity pixel matrix and non-periodicity pixel matrix. Next boundaries are created by connecting all the possible nearby periodicity …