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Journal : Building of Informatics, Technology and Science

Pengaruh Peningkatan Kualitas Citra Menggunakan Modifikasi Kontras Pada Kompresi Data RLE Lusiana, Veronica; Al Amin, Imam Husni; Sutanto, Felix Andreas
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (600.757 KB) | DOI: 10.47065/bits.v4i1.1646

Abstract

Data compression is needed so that the need for storage media and data transfer time becomes more efficient. This study compressed image data using the Run-Length Encoding (RLE) method. The test data is the original image (gray scale) and the image results of improving image quality (image enhancement) using contrast modification. Modification of contrast using contrast stretching methods. Through experiments wanting to know the extent to which the RLE method works less effectively for images with complex color intensity. The image of contrast modification results has a more complex color intensity or more varied pixel value. Obtained the number of pairs (p, q) RLE in the image of contrast modification results is less than the original image, with the pair ratio (p, q) RLE ranges from 0.64% to 1.59%. Although this image has a more varied pixel value than its original image, it can produce a compression ratio of the number of pairs (p, q) RLE.
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) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6418

Abstract

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.