Median and Laplacian Filters based Feature Analysis for Content Based Image Retrieval Using Color Histogram Refinement Method

Median and Laplacian filters are used to remove noise from images but some mount of information is also lost. Edge extraction and sharpening methods are used to restore the information lost by median and Laplacian filters. Histogram is used to extract features from filtered image but it has problem...

Full description

Saved in:
Bibliographic Details
Published inJournal of applied sciences (Asian Network for Scientific Information) Vol. 12; no. 5; pp. 416 - 427
Main Authors Malik, F, Baharudin, B
Format Journal Article
LanguageEnglish
Published 2012
Subjects
Color
Histograms
Mathematical analysis
Preserves
Retrieval
Similarity
Pakistan, Faisalabad
Online AccessGet full text

Cover

More Information
Summary:Median and Laplacian filters are used to remove noise from images but some mount of information is also lost. Edge extraction and sharpening methods are used to restore the information lost by median and Laplacian filters. Histogram is used to extract features from filtered image but it has problem that images with diverse appearance will have the same histograms because the spatial information in image does not preserve. To preserve spatial information, we quantize histograms into bins. In each bin the statistical features are calculated using the spatial information of regions. For similarity Sum-of-Absolute Differences (SAD) is used to calculate distance between query and database images. Retrieved images are displayed according to the optimized threshold value of the percentage of maximum of distance values. Experiments on the Corel database give results which show that the statistical features of histogram using spatial information are robust in retrieval of images based on Laplacian filter.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1812-5654
DOI:10.3923/jas.2012.416.427