| 基于改进 GLCM 的侧扫声纳影像分类研究 |
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| 引用本文： | 郭军,马金凤,王爱学.基于改进 GLCM 的侧扫声纳影像分类研究[J].测绘工程,2016,25(6):6-9. |
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| 作者姓名： | 郭军 马金凤 王爱学 |
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| 作者单位： | 国土资源部海底矿产资源重点实验室,广东 广州,510760;武汉大学 测绘学院,武汉,430079 |
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| 基金项目： | 广州海洋地质调查局区域调查项目(GZH201100312-01)；国土资源部海底矿产资源重点实验室开放基金资助项目(1212011220117) |
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| 摘 要： | 提出一种基于改进GLCM的算法IGLCM用于侧扫声纳影像的分类,IGLCM反映像素与其邻域像素的灰阶联合分布,全面描述像素与其邻域像素所在区域的纹理特征。利用GLCM和IGLCM分别提取4种纹理特征,应用支持向量机对侧扫声纳海底底质进行分类。研究结果表明,IGLCM分类精度优于GLCM,更适合侧扫声纳分类。
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| 关 键 词： | 侧扫声纳系统 灰度共生矩阵 纹理 分类 |
A study of side scan sonar image classification based on improved gray level co-occurrence matrix |
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| GUO Jun,MA Jinfeng,WANG Aixue.A study of side scan sonar image classification based on improved gray level co-occurrence matrix[J].Engineering of Surveying and Mapping,2016,25(6):6-9. |
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| Authors: | GUO Jun MA Jinfeng WANG Aixue |
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| Abstract: | An effective methodology for side scan sonar image classification based on improved GLCM , IGLCM ,is proposed .The method describes the spatial gray level dependence of a pixel and all of its neighborhood pixel ,and comprehensively presents the texture in pixel area .Four texture features are extracted by GLCM and IGLCM respectively ,and the side scan sonar classification is carried out with SVM .The result show that the proposed is superior and more suitable for side scan sonar classification compared with GLCM . |
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| Keywords: | side scan sonar system gray level co-occurrence matrix texture classification |
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