L. Jayanthi ¹, K. Lakshmi ¹, A. Kovalan ¹

Affiliations
1 School of Computing Science and Engineering, Periyar Maniammai University, Thanjavur - 613403, Tamil Nadu, IN

Abstract

Background/Objectives: Retrieving visually similar images from image database needs high speed and accuracy. Various text and content based image retrieval techniques are being investigated by the researchers in order to exactly match the image features. Methods/Statistical Analysis: The proposed technique deals with Content Based Image Retrieval (CBIR) system by applying various image feature detection and matching techniques to investigate the retrieving efficiency of the image. The newness in the proposed research is that it extracts image features like texture, color and shape by combining various angular rotation and image segmentation techniques. With the output of the rotation and segmentation algorithm, color histograms, straight line and outline features including vertical, angled and horizontal lines are extracted. Findings: The accuracy and performance related issues listed in the previous works are overcome while the database images grow. The results obtained by the proposed system obviously confirm that Partitioning and rotating of image objects helps in retrieving many numbers of similar images from the database. Conclusion/Improvements: The proposed CBIR method is compared with our previously existed methodologies and found better in the retrieval accuracy. The retrieval time and accuracy are comparatively good than previous works proposed in CBIR system.

Keywords

CBIR, Image Features, Outline Color Histogram, Rotation Mechanism, Segmentation, Straight Line

Full Text

   

A. Sampath Dakshina Murthy ¹, T. Pavani ², K. Lakshmi ¹

Affiliations
1 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN
2 Department of ECM, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, IN

Abstract

Several mathematical models are used for tracking reentry objects in case of radar and sonar. Bayes law evaluations by Unseen Markov Mannequin is one of these which can be used with compatible Kalman filters. To reduce linearization errors, in metaheurestic methods, a new algorithm is proposed by combination of stochastic and metheuristic techniques. For determination of estimation performance, Firefly Hybrid Extended Kalman Filter has been suggested. Convergence of such systems of firefly is quite high. These are compatible with nonlinear multimodal issues. Simulations studies have been done by MATLAB. The drag resistance is found to be related not only to speed but also to maximum cross sectional errors. The minimization of errors of altitude, velocity and ballistic coefficients are taken to be random. In comparison with Extended Kalman Filter and Hybrid Extended Kalman Filter, the results show 30 to 50 percent error reduction. Combinations of metaheurestic and stochastic methods have immense possibility of development of optimization in case of tracking of reentry objects.

Keywords

Ballistic Coefficient, Extended Kalman Filter, Firefly algorithm, Hybrid Extended Kalman Filter, Metaheurestic, Reentry objects.

Full Text