Open AccessDetecting Faces in Noisy Images using Hit-Miss Transform (HMT)
Author(s) -
Poornaiah Billa,
Anandbabu Gopatoti,
Kiran Kumar Gopathoti,
K.C Koteswaramma
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d4613.118419
Subject(s) - artificial intelligence , computer vision , computer science , noise (video) , face (sociological concept) , transformation (genetics) , object (grammar) , gaussian noise , object detection , pattern recognition (psychology) , image (mathematics) , homogeneous , sample (material) , mathematics , social science , biochemistry , chemistry , chromatography , combinatorics , sociology , gene
The object of this paper is to detect faces in noisy images. All sample images show homogeneous background faces. The transformation of the Hit-Miss is used to detect object boundaries and remove the noise effect. Two filters are cascaded to handle high noise levels in a special way. An application for face detection in noisy conditions is presented. The algorithm is implemented on faces taken from the Manchester face database after adding Gaussian noise to them.