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Sistem Temu Kembali Citra Berbasis Isi Menggunakan Metode Micro-Structure Descriptor (MSD) dan Grey Level Co-occurence Matrix (GLCM)
Abstract- Content based image retrieval (CBIR) is applications of image processing and computer vision that can help users to retrieve or searched images quickly based by queries or user desire on large database. This technique used a features of an image like color, texture, and shape. Those features will be used as the basis for checking or matching a similarity between images on database. In this research, we combined MSD and GLCM method proposed new method that combined MSD and GLCM to build CBIR system. The proposed method is used for extracting global and local features of images. MSD method can represent global features, while local features can represent by GLCM method. Then, we will be match the features use L1 Distance. In this research we used two kind of dataset there are batik and corel dataset, which is each of dataset contains 10.000 images. We compare this proposed method with MSD dan GLCM. The result show this proposed method better than MSD and GLCM, which is the average precision is 99,77% for batik dataset and 62,72% for corel dataset. In other word, this perposed method is effective for CBIR system.
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