JOURNAL ARTICLE

Object segmentation using graph cuts based edges features

Yuki MasumotoWeiwei DuNobuyuki Nakamori

Year: 2013 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 8655 Pages: 86550I-86550I   Publisher: SPIE

Abstract

The paper presents a simple graph cuts algorithm based edges features to object segmentation problems. The user gives some scribbles to background and foreground of an image. Gaussian mixture models(GMMs) are built based on the scribbles. The pixel without scribble belongs to the background or the foreground depending on the relative probability of each pixel. The contribution of our paper is to add edges features to GMMs. The approach is applied with images from the Grab cuts segmentation database. The approach is suitable for images with noise and in the foreground and background with similar colors.

Keywords:
Artificial intelligence Computer science Pixel Mixture model Cut Image segmentation Segmentation Computer vision Pattern recognition (psychology) Scale-space segmentation Graph Segmentation-based object categorization Object (grammar) Gaussian

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Topics

Bayesian Methods and Mixture Models
Physical Sciences →  Computer Science →  Artificial Intelligence

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