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All Journal International Journal of Electrical and Computer Engineering ComEngApp : Computer Engineering and Applications Journal Annual Research Seminar Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Generic

Saparudin Saparudin

Universitas Sriwijaya

Author-ID : 2373257

Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 11 Documents Claim Missing Document

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Segmentation of Fingerprint Image Based on Gradient Magnitude and Coherence Saparudin Saparudin; Ghazali Sulong
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 5: October 2015
Publisher : Institute of Advanced Engineering and Science

Fingerprint image segmentation is an important pre-processing step in automatic fingerprint recognition system. A well-designed fingerprint segmentation technique can improve the accuracy in collecting clear fingerprint area and mark noise areas. The traditional grey variance segmentation method is widely and easily used, but it can hardly segment fingerprints with low contrast of high noise. To overcome the low image contrast, combining two-block feature; mean of gradient magnitude and coherence, where the fingerprint image is segmented into background, foreground or noisy regions, has been done. Except for the noisy regions in the foreground, there are still such noises existed in the background whose coherences are low, and are mistakenly assigned as foreground. A novel segmentation method based on combination local mean of grey-scale and local variance of gradient magnitude is presented in this paper. The proposed extraction begins with normalization of the fingerprint. Then, it is followed by foreground region separation from the background. Finally, the gradient coherence approach is used to detect the noise regions existed in the foreground. Experimental results on NIST-Database14 fingerprint images indicate that the proposed method gives the impressive results.

Hybrid Multilevel Thresholding and Improved Harmony Search Algorithm for Segmentation Erwin Erwin; Saparudin Saparudin; Wulandari Saputri
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

This paper proposes a new method for image segmentation is hybrid multilevel thresholding and improved harmony search algorithm. Improved harmony search algorithm which is a method for finding vector solutions by increasing its accuracy. The proposed method looks for a random candidate solution, then its quality is evaluated through the Otsu objective function. Furthermore, the operator continues to evolve the solution candidate circuit until the optimal solution is found. The dataset used in this study is the retina dataset, tongue, lenna, baboon, and cameraman. The experimental results show that this method produces the high performance as seen from peak signal-to-noise ratio analysis (PNSR). The PNSR result for retinal image averaged 40.342 dB while for the average tongue image 35.340 dB. For lenna, baboon and cameramen produce an average of 33.781 dB, 33.499 dB, and 34.869 dB. Furthermore, the process of object recognition and identification is expected to use this method to produce a high degree of accuracy.

Real-time Multi-object Face Recognition Using Content Based Image Retrieval (CBIR) Muhammad Fachrurrozi; Saparudin Saparudin; Erwin Erwin; Mardiana Mardiana; Clara Fin Badillah; Junia Erlina; Auzan Lazuardi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Face recognition system in real time is divided into three processes, namely feature extraction, clustering, detection, and recognition. Each of these stages uses different methods, Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Multi-face image search using Content Based Image Retrieval (CBIR) method. CBIR performs image search by image feature itself. Based on real time trial results, the accuracy value obtained is 61.64%.

Co-Authors Ahmad Affandi Ahmad Fali Oklilas Arum Cantika Putri Auzan Lazuardi Clara Fin Badillah Darmawijoyo, Darmawijoyo Deris Stiawan Erwin Erwin Erwin, Erwin Fifi Hariyani Firdaus Firdaus Ghazali Sulong Hadi Purnawan Satria Hidayat Hidayat Julian Supardi Junia Erlina M. Fachrurrozi . Primanita, Anggina Reza Firsandaya Malik Rikza Azriyan Siti Nurmaini Sri Desy Siswanti Syamsuryadi Syamsuryadi Vikki Aria Dinata Wulandari Saputri Yoga Yuniadi

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Journal : International Journal of Electrical and Computer Engineering