Informatics Publishing Limited

Koppala Guravaiah ¹, M. Ramu ², A. Damodhar ³, B. D. Kalyan Kumar ²

Affiliations
1 Department of Information Technology, Sree Vidyanikethan Engineering College, Tirupati, AP, IN
2 Department of Computer science & Systems Engineering, Sree Vidyanikethan Engineering College, Tirupati, AP, IN
3 Department of Computer Science Engineering,, Sree Venkateswara College of Engineering, Tirupati, AP, IN
4 Department of Computer Science & Systems Engineering, Sree Vidyanikethan Engineering College, Tirupati, AP, IN

Abstract

Region filling is the most important in many applications like computer graphics, computer cartography, pattern recognition, and scene analysis. The conventional pixel based region filling algorithms like flood filling, boundary filling are the recursive algorithms and these algorithms have the ability to use an indefinite amount of stack space and can cause a system to become unstable. And these recursive algorithms are not suitable for filling the larger size polygons. The proposed algorithm using divide and conquer approach, divides the polygon into subparts and fills the subparts for solving the above difficulties. And finally we compare and present the results of existing and proposed algorithms.

Keywords

Polygon, Divide and Conquer, Region Filling, Raster Scan.

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Koppala Guravaiah ¹, B. Ramakantha Reddy ¹, S. Shiva Prakash ¹, M. Naveenkumar ¹

Affiliations
1 CSE Department, Sree Vidyanikethan Engineering College, Tirupati, AP, IN

Abstract

Team work plays major role in any organization for solving problem. We have many online collaborative systems for team communication. These systems generates huge amount of data. Our main aim is to find the best group and best person among the group. And also specify groups and their facilitators operation and provide feedback also for their outcomes and also specify about the problems. This is done by clustering the communication data and applies the sequential pattern mining technique on that data. By applying this techniques we easily finding that which team work is good and which team member work very well. Also specifies feedback system to week teams through analysing good team pattern mining.

Keywords

Data Mining, Clustering, Sequential Pattern Mining, Team Work, Tracking System (TRAC).

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