文章基本信息

标题：Face Recognition on Linear Motion-blurred Image
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作者：Fergyanto E. Gunawan ; Jeklin Harefa ; Nobumasa Sekishita 等
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2018
卷号：16
期号：3
页码：1249-1255
DOI：10.12928/telkomnika.v16i3.5480
语种：English
出版社：Universitas Ahmad Dahlan
其他摘要：Most face recognition algorithms are generally capable to achieve a high level of accuracy when the image is acquired under wellcontrolled conditions. The face should be still during the acquisition process; otherwise, the resulted image would be blur and hard for recognition. Enforcing persons to stand still during the process is impractical; extremely likely that recognition should be performed on a blurred image. It is important to understand the relation between the image blur and the recognition accuracy. The ORL Database was used in the study. All images were in PGM format of 92 × 112 pixels from forty different persons, ten images per person. Those images were randomly divided into training and testing datasets with 50-50 ratio. Singular value decomposition was used to extract the features. The images in the testing datasets were artificially blurred to represent a linear motion, and recognition was performed. The blurred images were also filtered using various methods. The accuracy levels of the recognition on the basis of the blurred faces and filtered faces were compared. The performed numerical study suggests that at its best, the image improvement processes are capable to improve the recognition accuracy level by less than five percent.
关键词：face recognition;image blurring;laplacian filter;singular value decomposition