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Multilevel-thresholding is an efficient method used in image segmentation. This paper presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation by integrating both the artificial bee colony (ABC) algorithm and the sine-cosine algorithm (SCA). The proposed algorithm, called ABCSCA, is applied to segment images and it utilizes Otsu's function as the objective function. The proposed ABCSCA uses ABC to optimize the threshold and to reduce the search region. Thereafter, the SCA algorithm uses the output of ABC to determine the global optimal solution, which represents the thresholding values. To evaluate the performance of the proposed ABCSCA, a set of experimental series is performed using nineteen images. In the first experimental series, the proposed ABCSCA is assessed at the low threshold levels and compared with the ABC and SCA as traditional methods. Moreover, the …