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- W2391211560 abstract "This paper presented a novelty classification method based on histogram of gradient( HOG) features and principle component analysis( PCA). Firstly,it extracted HOG features of image and whitened the features. At the second stage,it subsampled the features to an uniform scale,then extracted the image HOG features and projected these features into PCA space.At the last stage,it compared each test image with the PCA projections of training images,searched the nearest image comparing to the test image,finally it decided which class the test image belonged to and its max confidence scores. It implemented this method using C + +,and based on OpenCV 2. 4. 3 and Darwin 1. 3. 2 platform,tested this method on Pascal 2012 dataset with comparing to BOW-SVM method. The experiment shows this method has advantages both on running time and classification precision." @default.
- W2391211560 created "2016-06-24" @default.
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- W2391211560 date "2013-01-01" @default.
- W2391211560 modified "2023-10-03" @default.
- W2391211560 title "Effective image classification method based on HOG-PCA" @default.
- W2391211560 hasPublicationYear "2013" @default.
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