Removal of Specular Reflections in Tooth Color Image by Perceptron Neural Nets

摘要：

This study presents the removal algorithm of specular reflections in a tooth color image to eliminate the specularities which degrades the performance of color image segmentation algorithms. Our proposed methodology includes two tasks: (i) automated detection of specular reflections by Perceptron neural nets and (ii) recursive corrections of the specularities by applying a smoothing spatial filter on the target pixels (specular regions) based on the decision of Perceptron.

关键词： Specular reflections Perceptron neural nets Tooth Color Image

作者: Seong-Taek Lee Tae-Ho Yoon Kyeong-Seop Kim Kee-Deog Kim Wonse Park

作者单位: School of Biomedical Engineering Konkuk University Chungju, Korea School of BiomedicalEngineering Konkuk University Chungju, Korea Department of Advanced General Dentistry Yonsei University Seoul,Korea

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 285-289

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）