A SEGMENTATION ALGORITHM FOR THERMAL PAINT IMAGE

摘要：

Thermal paint is widely used for measuring surface temperature of devices in aeronautics and space industry, such as space shuttles engine, airplanes skin etc. The segmentation for the thermal paints image is the fundamentals of the digital and automated temperature measuring process. A new method for thermal paint image segmentation is proposed in this paper, which based on color and spatial information. First,PGF algorithm is selected to reduce images noises and keep the edge feature of image. Furthermore, using K-Means cluster algorithm, colors in the image are quantized to several representing classes that can be used to differentiate regions in the image. Finally, a region growing and merge method is then used to segment the image. Experimental results demonstrate that good segmentation is obtained by our algorithm, and our algorithm is suitable for segmenting the thermal paint image.

关键词： Image segmentation Thermal paint image Peer group filtering Color quantization Region growing

作者: NIAN-NIAN CHEN BO LI YONG FAN MAO-SONG LIN

作者单位: School of Computer Science and Techniques, South-West University of Science and Technology, MianYang, 621010,China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3842-3846

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）