A variational segmentation framework using active contours and thresholding

Segmentation involves separating distinct regions in an image. In this note, we present a novel variational approach to perform this task. We propose an energy functional that naturally combines two segmentation techniques usually applied separately: intensity thresholding and geometric active contours. Although our method can deal with more complex image statistics, intensity averages are used to separate regions, in this present work. The proposed approach affords interesting properties that can lead to sensible segmentation results. KEY WORDS Image segmentation, curve evolution, PDE, level-set methods, thresholding, parametric estimation.

• Type: Conference
• Year: 2007
• Where: SIP
• Authors: Samuel Dambreville, Marc Niethammer, Anthony J. Yezzi, Allen Tannenbaum
• Keywords: Image Processing, Intensity Thresholding, Segmentation Techniques, SIP 2007, WORDS Image Segmentation