Work place: Information Technology Department, Udayana University, Bali, Indonesia
E-mail: ayu_wirdi@yahoo.com
Website:
Research Interests: Image Processing, Image Manipulation, Image Compression, Computer systems and computational processes
Biography
Ni Kadek Ayu Wirdiani, Female, is a lecturer in Department of Information Technology, Udayana University Bali, Indonesia. She received her S.T degree in Communication Electronics, Electrical Engineering Department from Udayana University, Indonesia on 2004. She received her M.T degree in Information Technology Management, Electrical Engineering Department from Udayana University, Indonesia on 2011. Her research interests are Biometrics and Image Processing
By Ni Kadek Ayu Wirdiani Tita Lattifia I Kadek Supadma Boy Jehezekiel Kemanang Mahar Dewa Ayu Nadia Taradhita Adi Fahmi
DOI: https://doi.org/10.5815/ijigsp.2019.11.01, Pub. Date: 8 Nov. 2019
Real-time face image recognition is a face recognition system that is done directly using a webcam camera from a computer. Face recognition system aims to implement a biometrics system as a real-time facial recognition system. This system is divided into two important processes, namely the training process and the identification process. The registration process is a process where a user registered their name in a system and then registers their face. Face data that has been registered will be used for the next process, namely the identification process. The face registration process uses face detection using the OpenCV library. The feature extraction process and introduction to the recognition system use the Eigenface method. The results of this study found that, the Eigenface method is able to detect faces accurately up to 4 people simultaneously. The greater the threshold value will result in a greater value of FRR, while there isn’t any FAR value found from different thresholds. The level of lighting, poses, and facial distance from the camera when training and testing the face image heavily influences the use of the eigenface method.
[...] Read more.By I Wayan Agus Suryawibawa I Ketut Gede Darma Putra Ni Kadek Ayu Wirdiani
DOI: https://doi.org/10.5815/ijigsp.2015.02.01, Pub. Date: 8 Jan. 2015
Herbs are used in traditional medicine. There are so many herbs are spread across the world, it is difficult to memorize it all. This paper describes an android application to recognize herbs by their leaf characteristics (shape, veins, and keypoints). Shape and veins of leaves are recognized by Invariant Moment Method as the feature extraction. City Block Distance used to calculate the distance between the features. Whereas for detection and keypoints extraction using Oriented FAST and Rotated BRIEF on OpenCV library. This keypoints distance calculation using Brute-Force Hamming. Matching is done by calculating the shortest distance between test image and reference image. If the result is less than or equal to threshold then image is match. Experiment result show this application can achieve 79% of success rate by using keypoints. This result is influenced by glossy leaf surface, so there is many reflected light that become noise.
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