Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578197
Title: Performance comparison of min-max normalisation on frontal face detection using haar classifiers
Authors: Ali Garba Garba (UKM)
Jamilu Awwalu (UKM)
Haslina Arshad (UKM)
Lailatul Qadri Zakaria (UKM)
Keywords: Face detection
Haar classifier
Normalisation
Issue Date: Jun-2017
Description: Face detection and analysis is an important area in computer vision. Furthermore, face detection has been an active research field in the recent years following the advancement in digital image processing. The visualisation of visual entities or sub-pattern composition may become complex to visualise due to the high frequency of noise and light effect during examination. This study focuses on evaluating the ability of Haar classifier in detecting faces from three paired Min-Max values used on histogram stretching. Min-Max histogram stretching was the selected method for implementation given that it appears to be the appropriate technique from the observation carried out. Experimental results show that, 60-240 Min-Max values, Haar classifier can accurately detect faces compared to the two values.
News Source: Pertanika Journals
ISSN: 0128-7680
Volume: 25
Pages: 163-172
Publisher: Universiti Putra Malaysia Press
Appears in Collections:Journal Content Pages/ Kandungan Halaman Jurnal

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