A polynomial-time algorithm for image segmentation using Ising models
ICNC（2011）
摘要
The Ising model is a classical model and it has been used in a number of problem domains, such as statistical physics and computer vision. The minimum energy of the Ising model is useful, however the lowest-energy is difficult to solve for the reason of time. In this paper, we use a polynomial-time algorithm based on the Ising model, to obtain the lowest energy and segment images efficiently. Image segmentation is a complex problem. There are many methods to solve this problem. It is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. We will use the state of the Ising model to denote the image segmentation. The time complexity of this algorithm for image segmentation is polynomial-time.
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关键词
statistical physics,the ising model,perfect matching,the lowest energy,image segmentation,visual characteristics,computational complexity,planarity,computer vision,polynomial-time algorithm,pixel labeling,ising model,minimization,polynomial time,algorithm design,computer model,computational modeling,edge detection,time complexity,algorithm design and analysis,semiconductor device modeling
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