Flame Color Image Segmentation Based on Neural Network

摘要：

A novel method of flame color image segmentation based on multilayer feedforward network is proposed. The training sample sets select the color and location information of the flame image in HSV color model as features. After preprocessing the training samples are normalized and input to multilayer feedforward network. By training with LevenbergMarquardt algorithm the segmentation result is presented as a two-dimensional matrix which determines whether the pixel is a flame pixels or not with a suitable threshold. Experimental results show that the this method can segment flame image correctly, and is flexible to subsequent processing.

关键词： color image segmentation neural network LM algorithm flame image HSV

作者: Kang Feng Wang Yarning Zhao Yun

作者单位: Dept. of agricultural engineering, Zhejiang University, Hangzhou 310029, China Dept. of Information Dept. of Information and Electrics, Zhejiang Sci-Tech University, Hangzhou 310018 China Dept. of agricultural engineering, Zhejiang University, Hangzhou 310029, China Dept. of Mechanical E

会议类型: 国际会议

会议名称: 2009 International Forum on Computer Science-Technology and Applications(2009年国际计算机科学技术与应用论坛 IFCSTA 2009)

会议地点: 重庆

会议语种:英文

页码: 404-407

在线出版日期: 2009-12-25（万方平台首次上网日期，不代表论文的发表时间）