Volume : IV, Issue : VI, June - 2015
Natural Image Statistics with Low–Level Hierarchical Segmentation in Content based Image Classification
Sangeetha Mary, Suvya P
Abstract :
?is paper aims at providing the statistics of the natural images. ?e properties being considered include the geometric, photometric and topological characteristics of natural images. ?e image is segmented using a lowlevel hierarchical multiscale segmentation algorithm. ?e algorithm provides different regions of the image which are arranged in a tree structure called segmentation tree. ?e geometric, photometric and topological characteristics of the regions of natural images are studied to represent the statistics of region properties. Along with the statistical properties some features like color, texture, edges and wavelet information are taken into consideration using a discrete wavelet transform. ?ese statistical features are used to model a dataset of natural images by a probability density function. ?e model then used to train the dataset and finally for image classification
Keywords :
Natural image statistics photometric scale discrete wavelet transform probability density function image classification.
Article:
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DOI : 10.36106/ijsr
Cite This Article:
Sangeetha Mary,Suvya P Natural Image Statistics with Low-Level
Hierarchical Segmentation in Content based
Image Classification
International Journal of Scientific Research, Vol : 4, Issue : 6 June 2015
Number of Downloads : 1268
References :
Sangeetha Mary,Suvya P Natural Image Statistics with Low-Level Hierarchical Segmentation in Content based Image Classification International Journal of Scientific Research, Vol : 4, Issue : 6 June 2015
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