Publication | Closed Access
A Review: Contrast-Limited Adaptive Histogram Equalization (CLAHE) methods to help the application of face recognition
118
Citations
5
References
2018
Year
Face DetectionFacial Recognition SystemImage ProcessingImage AnalysisMachine VisionImage Capture ObjectEngineeringPattern RecognitionFacial Expression RecognitionBiometricsEye TrackingFace RecognitionComputer ScienceImage ForensicsImage EnhancementComputer VisionOptical Image Recognition
Image processing technology in hardware and software has a significant development in all aspects of human civilization. Image processing is growing rapidly in various fields such as medical image, Biometrics, Object identification, Object character recognition (OCR), and many more. One biometric technique in an application detects and recognizes faces. Objectives of face recognition include recognizing emotions, identifying offenders, applying to security systems, image processing to access a door as an application of computer and human interaction. The facial recognition system in this research was conducted live streaming using Local Binary Pattern Histogram (LBPH) method. There is a constraint to a light intake received by the camera through a sensor that captures the image. Based on the results of our research to make better facial recognition, we propose using adaptation methods on the intensity of light that is around the image capture object. The method of adaptation in this research is the Contrast Adaptive Limited Histogram (CLAHE).
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