Informatics Publishing Limited

R. Tamilkodi ¹, K. Valli Madhavi ¹, K. Jayasudha ²

Affiliations
1 Department of computer Applications, GIET, Rajahmundry.
2 Department of EXTC, SFIT, Mumbai.

Abstract

A methodology for the detection and removal of cracks on digitized paintings is presented in this paper. The cracks are detected by thresholding the output of the morphological top-hat transform. Afterwards, the thin dark brush strokes which have been misidentified as cracks are removed using Median Radial Basis Function (MRBF) neural network on hue and saturation data or a semi-automatic procedure based on region growing. Finally, crack filling using order statistics filters or controlled anisotropic diffusion is performed. The methodology has been shown to perform very well on digitized paintings suffering from cracks. Within limited testing, the accuracy of the detection and analysis of cracks is better with the proposed method than with conventional methods.

Keywords

Thresholding, Cracks, Digitized Paintings, Neural Networks, Median Radial Basis Function, Top Hat Transform, Statistics Filters, Cracks Detection

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K. Jayasudha ¹, C. Chandrasekar ²

Affiliations
1 Department of Computer Application,K. S. Rangasamy College of Technology, Tamilnadu,, IN
2 Periyar University, Salem, Tamilnadu, IN

Abstract

VANETs (Vehicular Ad hoc Networks) are highly mobile wireless ad hoc networks and will play an important role in public safety communications and commercial applications. Routing of data in VANETs is a challenging task due to rapidly changing topology and high speed mobility of vehicles. In VANET, the possible occurrence of link breakage event is unknown and unpredictable. In a packet forwarding event, one node could select a next forwarder from its neighbors. The neighbor node that was in the transmission range at the moment, but at the edge, could already have left this range and, choosing this neighbor as next forwarder will lead to low packet delivery, increased packet delay, and increased routing overhead. In this paper, we propose HCBGR (Hierarchical Clustering Based Greedy Routing), a greedy position based routing approach which uses weighted score based strategy for reliable and efficient packet forwarding. We propose Revival Mobility model (RMM) to evaluate the performance of our routing technique. The simulation results using ns 2.33 show that routing overhead is reduced considerably compared to Greedy Perimeter Stateless Routing Protocol (GPSRP) and Predictive Directional Greedy Routing Protocol (PDGRP) of VANET. The simulation results show that HCBGR had overcome the limitations of PDGRP and GPSRP in VANET environment.

Keywords

Vehicular Ad Hoc Networks, Greedy Position Based Routing, Clustering, HCBGR.

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K. Prasanth ¹, K. Duraiswamy ², K. Jayasudha ³, C. Chandrasekar ⁴

Affiliations
1 Dept of IT, K.S.Rangasamy College of Technology, Tiruchengode (T.N), IN
2 Dept of CSE, K.S.Rangasamy College of Technology, Tiruchengode (T.N), IN
3 Dept of Computer Applications, K.S.R College of Engineering, Tiruchengode (T.N), IN
4 Periyar University, Salem (T.N), IN

Abstract

Vehicular Ad-hoc Networks (VANETs) have been recently attracting an increasing attention from both research and industry communities. VANETs are currently deployed on a large scale, research in this area is mostly simulation based. Mobility models or the movement patterns of nodes communicating wirelessly, play a vital role in determining the protocol performance in VANET. We still have a limited understanding of the required level of mobility details for modeling and simulating VANETs. Thus, it is essential to study and analyze various mobility models and their effect on VANET protocols. In this paper, we examine d different mobility models proposed in the recent research literature. We proposed Revival Mobility Model (RMM) and evaluate its effect on packet delivery in VANETs by ns-2 simulations.

Keywords

Vehicular Ad Hoc Networks, Mobility Modeling, Revival Mobility Model, Packet Delivery Ratio.

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