TY - GEN
T1 - Morphological Preprocessing for Low-Resolution Face Recognition using Common Space
AU - Marzani, Ghali
AU - Suciati, Nanik
AU - Hidayati, Shintami Chusnul
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/2
Y1 - 2021/8/2
N2 - There are many researches on face recognition, but most have not produced satisfactory results on very low-resolution images. This study proposes the use of morphological preprocessing to improve the performance of common space approach for face recognition on low-resolution images. The morphological preprocessing consists of Top-Hat and Bottom-Hat Transformations, which capable of extracting small elements and handling uneven lighting on images. The k-Nearest Neighbor is used to recognize the face by measuring the distance of deep CNN features of low and high-resolution images in the common space. Experiment on the Yale Face dataset shows that the use of Morphological Preprocessing can increase the face recognition accuracy by 14.59%, 1.00%, and 2.50% for low-resolution images with sizes 24x24, 36x35, and 56x56, respectively.
AB - There are many researches on face recognition, but most have not produced satisfactory results on very low-resolution images. This study proposes the use of morphological preprocessing to improve the performance of common space approach for face recognition on low-resolution images. The morphological preprocessing consists of Top-Hat and Bottom-Hat Transformations, which capable of extracting small elements and handling uneven lighting on images. The k-Nearest Neighbor is used to recognize the face by measuring the distance of deep CNN features of low and high-resolution images in the common space. Experiment on the Yale Face dataset shows that the use of Morphological Preprocessing can increase the face recognition accuracy by 14.59%, 1.00%, and 2.50% for low-resolution images with sizes 24x24, 36x35, and 56x56, respectively.
KW - face recognition
KW - low-resolution
KW - morphological
KW - preprocessing
UR - http://www.scopus.com/inward/record.url?scp=85116090092&partnerID=8YFLogxK
U2 - 10.1109/ICISS53185.2021.9533241
DO - 10.1109/ICISS53185.2021.9533241
M3 - Conference contribution
AN - SCOPUS:85116090092
T3 - 8th International Conference on ICT for Smart Society: Digital Twin for Smart Society, ICISS 2021 - Proceeding
BT - 8th International Conference on ICT for Smart Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on ICT for Smart Society, ICISS 2021
Y2 - 2 August 2021 through 4 August 2021
ER -