Bins Formation using CG based Partitioning of Histogram Modified Using Proposed Polynomial
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2012, Vol 3, Issue 5
Abstract
This paper proposes a novel polynomial transform to modify the original histogram of the image to adjust the pixel density equally towards the high intensity levels so that uniform distribution of the pixels can be obtained and the image can be enhanced. We have shown the efficient use of this modified histogram for Content Based Image Retrieval. According to the CBIR system described in this paper each image is separated into R, G and B plane and for each plane a modified histogram is calculated. This modified histogram is partitioned into two parts by calculating the Center of gravity and using it 8 bins are formed on the basis of R, G and B values. These 8 bins are holding the count of pixels falling into particular range of intensity levels separated into two parts of the histogram. This count of pixels in 8 bins is used as feature vector of dimension 8 for comparison to facilitate the image retrieval process. Further these bins data is used to form the new variations of feature vectors ; Total (sum) and Mean of pixel intensities of all the pixels counted in each of the 8 bins. These feature vector variation has also produced good image retrieval. This paper compares the proposed system designed using the CG based partitioning of the original and histogram modified using the polynomial transform for formation of the 8 bins which are holding the Count of pixels and Total and Mean of intensities of these pixels. This CBIR system is tested using 200 query images from 20 different classes over database of 2000 BMP images. Query and database image feature vectors are compared using three similarity measures namely Euclidean distance, Cosine Correlation distance and Absolute distance. Performance of the system is evaluated using three parameters PRCP (Precision Recall Cross-over Point), LSRR (Length of String to Retrieve all Relevant images) and Longest String
Authors and Affiliations
H. B. kekre, Kavita Sonawane
Keywords
Related Articles
- EP ID EP150859
- DOI -
- Views 69
- Downloads 0
An Interoperable Data Framework to Manipulate the Smart City Data using Semantic Technologies
During the last decade, enormous volumes of urban data have been produced by the Government agencies, the NGOs and the citizens. In such a scenario, we are presented with a diverse sets of data which holds valuable infor...
Coverage-Aware Protocols in Wireless Sensor Networks: A Review
Coverage plays a vital role in wireless sensor networks (WSNs), since it is used as one of the important measure to achieve the performance of the sensor network. The sensor nodes in WSN have limited power and energy res...
A Study of Feature Selection Algorithms for Predicting Students Academic Performance
The main aim of all the educational organizations is to improve the quality of education and elevate the academic performance of students. Educational Data Mining (EDM) is a growing research field which helps academic in...
Arabic Sign Language (ArSL) Recognition System Using HMM
Hand gestures enabling deaf people to communication during their daily lives rather than by speaking. A sign language is a language which, instead of using sound, uses visually transmitted gesture signs which simultaneou...
Neural Network Based Lna Design for Mobile Satellite Receiver
Paper presents a Neural Network Modelling approach to microwave LNA design. To acknowledge the specifications of the amplifier, Mobile Satellite Systems are analyzed. Scattering parameters of the LNA in the frequency ran...