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BW = lazysnapping(A,L,foremask,backmask) segments the image A into foreground and background regions using lazy snapping. The label matrix L specifies the subregions of the image. foremask and backmask are masks desig...
Basic Algorithm Graph Cut: The algorithm for lazy snapping is implemented using (1) extraction of seed pixels, (2) K-means clustering and (3) Probability calculation. It takes the main image, stroke image and k value ...
Nov 2, 2022 · 文章浏览阅读783次，点赞2次，收藏3次。LazySnapping算法是一种图像分割方法，结合分水岭算法和k-means聚类，通过用户交互指定前景背景。算法包括似然能量和边界能量的定义，以及最小割模型的应用。实验表明该算法速度快但存在边界毛边和小区域分割错误的问题，可通过用户交互和阈值处理进行 ...
Abstract In this paper, we present Lazy Snapping, an interactive image cutout tool. Lazy Snapping separates coarse and fine scale processing, making object specification and detailed adjustment easy. More-over, Lazy S...
Aug 1, 2004 · In this paper, we present Lazy Snapping, an interactive image cutout tool. Lazy Snapping separates coarse and fine scale processing, making object specification and detailed adjustment easy. Moreover, La...
The C++ implementation for lazy snapping, an interactive image-cut out tool based on the algorithm proposed by Yin Li, Jian Sun, Chi-Keung Tang, Heung-Yeung Shum - GitHub - vyerneni/LazySnapping: ...
Feb 27, 2017 · 文章浏览阅读4k次。本文介绍了一种基于超像素的交互式图像分割方法——LazySnapping。该方法使用分水岭算法预处理图像并将其分割成多个小区域，然后通过用户标记的前景和背景像素点进行初步分割，并采用GraphCut优化算法进一步细化边界。此方法能显著提高处理速度。
