کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6941551 1450113 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Weak boundary preserved superpixel segmentation based on directed graph clustering
ترجمه فارسی عنوان
مرز ضعیف تقسیم بندی سوپرپیکسل های حفظ شده بر اساس خوشه بندی گراف کارگردانی شده است
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Weak boundary preservation is a challenge for superpixel segmentation. Existing methods that measure pixels' similarity based on pairwise distance could not efficiently describe relationship among high-dimensional image data, which plays key roles in extraction for image boundaries. In this paper, we present a new directed graph clustering (DGC)-based superpixel segmentation method via K-nearest-neighbor (K-NN) graph and distance information. It can efficiently deal with segmentation for the weak boundary of complex and irregular object. The basic idea is motivated by following observations: compared with smooth region, image boundary points have much lower pixel density and directed connectivity in local region. Based on K-NN directed graph, we introduce indegree and outdegree to describe above observation, which are the foundation to evaluate pixels' similarity. Then, a patch-based segmentation generates superpixel borders by even overlapping regions. Finally, we solve an integer programming to stitch small noise regions into final superpixels. Experimental results on two benchmarks demonstrate that our method outperforms the state-of-the-arts.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 65, July 2018, Pages 231-239
نویسندگان
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