Aerial Image Clustering Analysis Based on Genetic Fuzzy C-Means Algorithm and Gabor-Gist Descriptor

摘要：

　　In the study of identifying homogeneous regions in remote sensing images,fuzzy clustering is one of the most frequently used algorithms.Commonly used method of fuzzy cluster analysis is the fuzzy C-means algorithm(FCM),which easily traps into local optimal solution.An algorithm combining FCM with genetic algorithms is introduced for aerial remote sensing image fuzzy clustering analysis.The input image features are extracted based on a new descriptor which combines Gabor descriptor with Gist descriptor.The dimension reduction of the extracted feature vector is processed through principal component analysis.Then the extracted features from in-house aerial images dataset are clustered with proposed method.Experiment shows that this method can get a good clustering effect.

关键词： aerial image classification genetic algorithm fuzzy clustering Gabor-Gist descriptor

作者: Zhiming Shang Zhaorong Lin Gaojin Wen Na Yao Chunxiao Zhang Qian Zhang

作者单位: Beijing Institute of Space Mechanics and Electricity Beijing,China

会议类型: 国际会议

会议名称: The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

会议地点: 厦门

会议语种:英文

页码: 76-80

在线出版日期: 2014-08-19（万方平台首次上网日期，不代表论文的发表时间）