کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533406 870113 2012 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Image representation for generic object recognition using higher-order local autocorrelation features on posterior probability images
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Image representation for generic object recognition using higher-order local autocorrelation features on posterior probability images
چکیده انگلیسی

This paper presents a novel image representation method for generic object recognition by using higher-order local autocorrelations on posterior probability images. The proposed method is an extension of the bag-of-features approach to posterior probability images. The standard bag-of-features approach is approximately thought of as a method that classifies an image to a category whose sum of posterior probabilities on a posterior probability image is maximum. However, by using local autocorrelations of posterior probability images, the proposed method extracts richer information than the standard bag-of-features. Experimental results reveal that the proposed method exhibits higher classification performances than the standard bag-of-features method.


► Proposed an image description method using HLAC feature on posterior probability images.
► The proposed method overcomes the limitation of spatial information of the bag-of-features.
► The proposed method exhibits higher classification performances than the bag-of-features.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 45, Issue 2, February 2012, Pages 707–719
نویسندگان
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