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Universitas Hasanuddin
Research output:Contribution to journalArticlepeer-review

Face recognition of low-resolution video using gabor filter adaptive histogram equalization

Sino H.W.

Proceeding 2019 International Conference of Artificial Intelligence and Information Technology Icaiit 2019

Published: 2019Citations: 4

Abstract

The increasing of CCTV usage for handling security's problems has prompted the demand for face recognition system. Therefore, face recognition with low-resolution data from CCTV is needed. In this study, Viola Jones, Gabor filter and Support Vector Machine (SVM) is used for face detection, feature extraction, and classification, respectively. Adaptive Histogram Equalization (AHE) is applied in the preprocessing stage to increase the recognition accuracy. With the implementation of AHE, the accuracy is increased from 82.85% to 97.14% for class (person) 1. The data in this study consist of 11 classes (people) where each of them has 50 training data and 70 testing data with the image size of 32x32 pixel.

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Artificial intelligenceSciences
Facial recognition systemSciences
Histogram equalizationSciences
Computer scienceSciences
Pattern recognition (psychology)Sciences
HistogramSciences
Computer visionSciences
Gabor filterSciences
Feature extractionSciences
Support vector machineSciences
PreprocessorSciences
Face (sociological concept)Sciences
Adaptive histogram equalizationSciences
PixelSciences
Face detectionSciences
Image (mathematics)Sciences
Social scienceSciences
SociologySciences