Guided lazy snapping for long thin object selection

¹ Department of Electronics, Myongji University, Yongin-si Gyeonggi-do, Korea
² Department of Computer Science, FPT University, Hanoi, Vietnam

Corresponding author: sdsphoto@mju.ac.kr

Abstract

We show a novel way to select long thin objects in an image by enhancing the output of the existing foreground/background image segmentation methods. Most superpixel-based methods fail to select the long thin details, such as legs and whiskers, and extended curves from the main objects. We observe, however, the output without long thin details, can be used as the guided information to obtain the connected components. Based on this observation, our Guided Lazy Snapping method overcomes the limitation of the Lazy Snapping methods (or other alternatives superpixel-based segmentation method) to select long thin objects. The results show that connected components in the image can be selected without having a lot of user interactions (mouse clicks) on each extended parts of the object.