# Face recognition of low-resolution video using gabor filter adaptive histogram equalization
> Sino H.W.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85073144032
Jurnal / Konferensi: Proceeding 2019 International Conference of Artificial Intelligence and Information Technology Icaiit 2019
Tahun terbit: 2019
DOI: https://doi.org/10.1109/ICAIIT.2019.8834558
Citations: 4

## Authors
- Sino H.W.

## 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.

## Keywords
- Artificial intelligence
- Facial recognition system
- Histogram equalization
- Computer science
- Pattern recognition (psychology)
- Histogram
- Computer vision
- Gabor filter
- Feature extraction
- Support vector machine
- Preprocessor
- Face (sociological concept)
- Adaptive histogram equalization
- Pixel
- Face detection
- Image (mathematics)
- Social science
- Sociology

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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