Boosting the Accuracy of AdaBoost for Object Detection and Recognition

被引:0
|
作者
Mahrnood, Zahid [1 ]
Nazeer, Muhammad [2 ]
Arif, Muhammad [1 ]
Shahzad, Imran [1 ]
Khan, Fahad [1 ]
Ali, Mazhar [3 ]
Khan, Uzair [1 ]
Khan, Samee U. [4 ]
机构
[1] COMSATS Inst Informat Technol, Dept Elect Engn, Abbottabad, Pakistan
[2] COMSATS Inst Informat Technol, Dept Math, Wah Cantt, Pakistan
[3] COMSATS Inst Informat Technol, Dept Comp Sci, Abbottabad, Pakistan
[4] North Dakota State Univ, Dept Elect & Comp Engn, Fargo, ND USA
关键词
AdaBoost; Multi-Scale Retinex; Object Detection and Recognition; FACE; IDENTIFICATION;
D O I
10.1109/FIT.2016.25
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Recently, large number of object detection and recognition algorithms are playing a key role in several applications, such as security and surveillance. Although, these algorithms perform exceptionally well under normal lighting conditions, however their detection and recognition accuracy abruptly degrades under non-uniform illuminations, such as strong sunlight and bad lighting conditions. In this paper, we apply our own developed Multi-Scale Retinex (MSR) algorithm as a pre-processing module to boost the accuracy of the AdaBoost algorithm, which is considered to be state-of-the-art algorithm for robust object detection and recognition. Simulation results show that the MSR can be reliably and effectively used under non-uniform illuminations to boost the accuracy of the AdaBoost.
引用
收藏
页码:105 / 110
页数:6
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