Dwi Ratna Sulistyaningrum
Departemen Matematika, Fakultas Matematka, Komputasi Dan Sains Data, Institut Teknologi Sepuluh Nopember (ITS)

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Journal : International Journal of Computing Science and Applied Mathematics

Application of Daubechies Wavelet Transformation for Noise Rain Reduction on the Video Siti Khotijah; Dwi Ratna Sulistyaningrum
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 5, No 1 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1646.066 KB) | DOI: 10.12962/j24775401.v5i1.3549

Abstract

Currently, the use of digital video in the field of computer science is increasingly widespread, such as the process of tracking objects, the calculation of the number of vehicles, the classification of vehicle types, vehicle speed estimation and so forth. The process of taking digital video is often influenced by bad weather, such rain. Rain in digital video is considered noise because it is able to block objects being observed. Therefore, a rainfall noise reduction process is required in the video. In this study, the reduction of rain noise in digital video is using Daubechies wavelet transformation through several processes, namely: wavelet decomposition, fusion process, thresholding process and reconstruction process. The threshold value used in the thresholding process is VishuShrink, BayesShrink, and NormalShrink. The result of the implementation and noise reduction test show that Daubechies db2 level 3 filter gives the result with the biggest PSNR value. As for the type of threshold that provides optimal results is VishuShrink.
Texture-Based Woven Image Classification using Fuzzy C-Means Algorithm Soetrisno Soetrisno; Dwi Ratna Sulistyaningrum; Isi Bifawa’idati
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 8, No 1 (2022)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v8i1.9588

Abstract

There are a lot of texture-based image data stored in the storage media Internet. Most of these data portray the cultural fabric texture results from a State. Because of the many variants of the existing texture, the data need to be easily accessible through the Internet. Moreover, the area of origin of weaving the surface is easily known. Therefore, it is necessary to develop a classification system based on woven image data. The texture of the image data stored in a database on the Internet can be grouped/clustered well, making it easy to access. This study examines a texture-based woven image classification using fuzzy c-means algorithm. This method combines extraction methods Gabor filter, fuzzy c-means algorithm and Euclid distance similarity measure. An experiment was done using the system as many as 60 woven images from Bali, NTT and Central Java areas, each taken as many as 25 images weaving. The test results stated that testing using the test images taken from the images in the database generates a 100% accuracy rate, and testing using test images taken from outside the database produces an accuracy rate of 94%.