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题名: Local Line Derivative Pattern For Face Recognition
作者: Zhichao Lian ; Meng Joo Er ; Cong Y(丛杨)
作者部门: 机器人学研究室
会议名称: 2012 IEEE International Conference on Image Processing
会议日期: September 30 - October 3, 2012
会议地点: Orland, Florida, USA
会议主办者: IEEE Signal Processing Society
会议录: Proceedings of the 2012 IEEE International Conference on Image Processing
会议录出版者: IEEE
会议录出版地: New York, USA
出版日期: 2012
页码: 1449-1452
收录类别: EI
ISBN号: 978-1-4673-2533-2
关键词: Face recognition ; High-order local pattern ; Local binary pattern
摘要: In this paper, we propose a novel face descriptor for face recognition, named Local Line Derivative Pattern (LLDP). High-order derivative images in two directions are obtained by convolving original images with Sobel Masks. A revised binary coding function is proposed and three standards on arranging the weights are also proposed. Based on the standards, the weights of a line neighborhood in two directions are arranged. The LLDP labels in two directions are calculated with the proposed binary coding function and weights. The labeled image is divided into blocks where spatial histograms are extracted separately and concatenated into an entire histogram as features for recognition. The experiments on the FERET and Extended Yale B show superior performances of the proposed LLDP compared to other existing methods based on the LBP. The results prove that the LLDP has good robustness against expression, illumination and aging variations.
产权排序: 2
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/10208
Appears in Collections:机器人学研究室_会议论文

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