|Table of Contents|

Image classification algorithm based on spatial probability product kernel

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2014年03期
Page:
325-
Research Field:
Publishing date:

Info

Title:
Image classification algorithm based on spatial probability product kernel
Author(s):
Yang SaiZhao Chunxia
School of Computer Science and Engineering,NUST,Nanjing 210094,China
Keywords:
spatial probability product kernelimage classificationbagofwordsstatistic pooling methodstatistical informationspatial informationParzen window methodprobability distributionskernel matricessupport vector machines
PACS:
TP319.7
DOI:
-
Abstract:
Aiming at the problems that the statistic pooling method using bagofwords(BoW) discards a lot of statistical and spatial information of coded vectors and only interacts with the standard kernel function to measure similarities of images,a spatial probability product kernel based image classification(SPPKBIC) algorithm is proposed here.The probability distributions of coded vectors are estimated by Parzen window method to describe images.The kernel matrices of images are calculated using the spatial probability product kernel function.Images are classified by support vector machines based on the kernel matrices.The experimental results show that the average classification accuracy of the SPPKBIG algorithm for scene 15 dataset and MSRcv2 dataset reach 84.1% and 94.8% respectively.

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Last Update: 2014-06-30