Improved Edge Detection Algorithm Based on Decision Tree

Abstract:

The edge detection is the important role in the image disposal. Traditional methods had some limitations more or less in practical applications such as pseudo-edge or need setting parameters by manual.Now, proposed a method can solve these problems in this paper. The histogram of gradient effective features was selected to composite the feature space, and during the process of classifier training, combined with AdaBoost and decision tree algorithm to improve the classification accuracy. Finally, the application of the algorithm proposed to image of Lena edge detection and comparative experimental show that the algorithm has better self-adaptability and good edge can be detected through this new algorithm.

• Periodical: Applied Mechanics and Materials (Volumes 321-324)
• Pages: 1080-1084
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.321-324.1080
• Online since: June 2013
• Authors: Ai Ping Cai
• Keywords: Adaboost Algorithm, Decision Tree Algorithm, Edge Detection

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