Temu Kembali Citra Makanan Menggunakan Ekstraksi Fitur Gray Level Co-occurrence Matrix dan CIE L*a*b* Color Moments Untuk Pencarian Resep Masakan - Ahmad Fauzi Ahsani; Yuita Arum Sari; Putra Pandu Adikara (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Recipes retrieval is an important thing in this technological era. Many people use search engine to find preferred food recipes. However, most people still use text query to search. Query text have many disadvantages, one of them is the lack of representation of food object because each person will be different in describing food. This problem can be solved if given query is an image of the food itself. This technique commonly referred as Content Based Image Retrieval. This study proposes image retrieval for cooking recipe searching using Gray Level Co-occurrence Matrix (GLCM) as a texture feature extraction method and CIE L*a*b* Color Moments as a color feature extraction method. The result of this study indicate that the MAP value is 97,604% when using combination of texture and color features, Minkowski distance algorithm and k = 10 with 1303 images of data training and 31 images of data testing. Based on these results, it can be concluded that GLCM and CIE L*a*b* color moments can be used on food image retrieval for searching cooking recipes.