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A crescent model is proposed for chick wing image processing and feather pattern recognition, thereby implementing chick sex separation by machine vision technology. The crescent shape delineates the region of interest in a wing image by an arc of large radius and an arc of small radius at two off-centred circles. Wing feathers are divergently distributed in the crescent region, manifesting as an oriented stripe pattern. Male chick feathers gradually change in length from short to long and then to short in accordance with the crescent envelope. Female chick feathers alternate the stripe lengths, following a long-short-long stripe pattern. Based on this knowledge, a chick feather pattern can be numerically characterised by a stripe length sequence and a stripe endpoint sequence. For pattern classification, the first-order differences of these two sequences are used. The mean value of the stripe endpoint difference sequence is the most efficient feature in male-female chick classification. Experimental results justified the model and feature selection strategy, and showed the feasibility of automatic chick sex separation.