Adaptive image segmentation by using mean-shift and evolutionary optimisation

作者：Liu, Cong^*; Zhou, Aimin; Zhang, Qian; Zhang, Guixu

来源：IET Image Processing, 2014, 8(6): 327-333.

DOI：10.1049/iet-ipr.2013.0195

• Adaptive approach
• Adaptive image segmentation
• Adaptive strategy
• Evolutionary optimisation
• Fitness functions
• Optimal number
• Over segmentation
• Segmentation methods

Undersegmentation or oversegmentation is a challenge faced in image segmentation methods, and it is extreme important to determine the optimal number of regions (clusters) of an image in real-world applications. In this study, we introduce an adaptive strategy to do so. The basic idea is to firstly oversegment an image by using the Mean-shift (MS) method, and then segment the obtained oversegmented results by using an evolutionary algorithm. In the second stage, a feature is extracted for each region obtained by the MS method, and a new fitness function is designed to determine the optimal number of clusters. The adaptive approach is applied to a variety of images, and the experimental results show that our method is both efficient and effective for image segmentation.

• 出版日期2014-6
• 单位华东师范大学