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All Journal IAES International Journal of Robotics and Automation (IJRA) Jurnal Informatika Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Sisfokom (Sistem Informasi dan Komputer) Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi)
Mulyanto Mulyanto
Politeknik Negeri Samarinda
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

 1 
A Gray-Level Dynamic Range Modification Technique for Image Feature Extraction Using Fuzzy Membership Function Arief Bramanto Wicaksono Putra; Rheo Malani; Mulyanto Mulyanto
Indonesian Journal of Artificial Intelligence and Data Mining Vol 1, No 1 (2018): March 2018
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (734.317 KB) | DOI: 10.24014/ijaidm.v1i1.4599

Abstract

The features of an image must be unique so it is necessary to use certain techniques to ensure them. One of the common techniques is to modify the gray dynamic range of an image. In principle, the gray level dynamic range modification maps the gray level ranges from the input image to the new gray level range as an output image using a specific function. Fuzzy Membership Function (MF) is one kind of membership function that applies the Fuzzy Logic concept. This study uses Trapezoidal MF to map the gray dynamic range of each RGB component to produce a feature of an RGB image. The aim of this study is how to ensure the uniqueness of image features through the setting of Trapezoidal MF parameters to obtain the new dynamic range of gray levels that minimize the possibility of other features other than the selected feature. To test the performance of the proposed method, it also tries to be applied to the signature image. Mean Absolute Error (MAE) calculations between feature labels are performed to test authentication between signatures. The results obtained are for comparison of samples of signature images derived from the same source having a much smaller MAE than the comparison of samples of signature images originating from different sources.
Co-Authors Abdul Najib Achmad Aulia Rachman Achmad Fanany Onnilita Gaffar Adji Santoso Malani, Rheo Muhammad Taufiq Sumadi Sri Ayu Susanti Suprapty, Bedi