Otsu based Multi-level Image Segmentation using Brownian Bat Algorithm
نویسندگان
چکیده
In this work, bi-level and multi-level segmentation is proposed for the grey image dataset using a novel Brownian Bat Algorithm (BBA). Maximization of Otsu's between-class variance function is chosen as the objective function. The performance of the proposed CBA is demonstrated by considering five benchmark images and compared with the existing bat algorithms such as Traditional Bat Algorithm (TBA) and the Lévy flight Bat Algorithm (LBA).
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