Title :
Removal of specular reflections in tooth color image by perceptron neural nets
Author :
Lee, Seong-Taek ; Yoon, Tae-Ho ; Kim, Kyeong-Seop ; Kim, Kee-Deog ; Park, Wonse
Author_Institution :
Sch. of Biomed. Eng., Konkuk Univ., Chungju, South Korea
Abstract :
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.
Keywords :
dentistry; image colour analysis; image segmentation; image sequences; perceptrons; color image segmentation algorithms; perceptron neural nets; removal algorithm; smoothing spatial filter; specular reflections; tooth color image; Color; Image color analysis; Mathematical model; Pixel; Reflection; Smoothing methods; Teeth; Perceptron neural nets; Specular reflections; Tooth Color Image;
Conference_Titel :
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-6892-8
Electronic_ISBN :
978-1-4244-6893-5
DOI :
10.1109/ICSPS.2010.5555624