Peningkatan Akurasi Temu Kembali Citra Berbasis Konten dengan Modifikasi Kontras Histogram Equalization dan Fast Fourier Transform - Hartono, Budi; Lusiana, Veronica; Eniyati, Sri (Building of Informatics, Technology and Science (BITS), 2024)
Image retrieval is a way to search for images in an image database based on the content or contents of the image or Content-Based Image Retrieval (CBIR). This study aims to develop a retrieval system using Fast Fourier Transform (FFT) for image texture feature extraction. The test image and image database consist of four Batik motif textures—contrast modification using Histogram Equalization. The level of similarity between the test image and the image database is calculated using Manhattan Distance. The study results show a difference in the accuracy of the retrieval results between images without and with contrast modification. In images with contrast modification, the accuracy of the search results increases by 71.4%. System performance is evaluated based on the level of accuracy calculated using the Precision, Recall, and F1-score values. Further research is still needed to test the accuracy of image retrieval results, especially in pre-processing image textures with other batik motifs.