Image texture classification and retrieval using self-organizing map

Vishal S. Thakare, N. Patil
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引用次数: 1

Abstract

Nowadays there has been great interest in field of image texture classification and retrieval. The increasing use of digital images has increased the size of image database which resulted in the need to develop a system that will classify and retrieve the required image of interest efficiently and accurately. This paper presents an effective and accurate method to classify and retrieve image using Self-organizing maps (SOM). The proposed method employs two phases, in the first phase color histogram is used to extract the color features and then the extracted features are given to Self-organizing map for initial classification. In the second phase Gray level co-occurrence matrix (GLCM) is used to extract the texture information from all images in each class from initial classification and then again given to Self-organizing map for final classification. The experimental results show the efficiency of the proposed method.
基于自组织映射的图像纹理分类与检索
目前,图像纹理分类与检索已成为人们关注的热点。随着数字图像的使用越来越多,图像数据库的规模也越来越大,因此需要开发一种能够高效、准确地分类和检索所需图像的系统。提出了一种有效、准确的图像分类检索方法——自组织映射(SOM)。该方法分为两个阶段,第一阶段使用颜色直方图提取颜色特征,然后将提取的特征交给自组织图进行初始分类。在第二阶段,利用灰度共生矩阵(GLCM)从初始分类的每一类图像中提取纹理信息,然后再将其转化为自组织图进行最终分类。实验结果表明了该方法的有效性。
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