Iterated Graph Cut Integrating Texture Characterization for Interactive Image Segmentation

An, Ning-Yu; Pun, Chi‐Man

doi:10.1109/cgiv.2013.34

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…Graph-based learning methods have been extensively proposed for image segmentation [1,9,10,18,37,53,54,56,59] and classification [49,[61][62][63] . Additionally, texture images have Table 1 Notation summary for the paper.…”

Section: Related Workmentioning

confidence: 99%

Texture recognition based on diffusion in networks

Gonçalves

Silva

Costa

et al. 2016

Information Sciences

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Section: Related Workmentioning

confidence: 99%

Texture recognition based on diffusion in networks

Gonçalves

Silva

Costa

et al. 2016

Information Sciences

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“…On this basis, Rother et al [4] developed the GrabCut algorithm. An [5] introduced the texture features of the object to the energy function of graph cut algorithm. Hou [6] combined the graph cut algorithm with the level set technique.…”

Section: Introductionmentioning

confidence: 99%

Fusion Between Shape Prior and Graph Cut for Vehicle Image Segmentation

Wu¹,

Sun²,

Liu³

et al. 2020

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In vehicle image segmentation, the traditional graph cut algorithm often have errors, when the original image contains shadows or complex background. To overcome the errors, this paper introduces the shape prior to graph cut algorithm. Our algorithm firstly maps the vehicle image to a weighted undirected graph, and obtains the regional energy and boundary energy functions. Then, the shape prior was added to constrain the image segmentation, and create a new energy function. The star convex was selected as the shape prior, and manually marked. Experimental results show that our algorithm segmented complex background vehicle images, shadowed vehicle images, and incomplete vehicle images more effectively than Otsu's method and graph cut algorithm. The details of vehicles were preserved and extracted efficiently by our algorithm. The research results provide new insights into vehicle image segmentation.

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Application of an Improved Grab Cut Method in Tongue Image Segmentation

Liu

Zhang

et al. 2018

Intelligent Computing Methodologies

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Iterated Graph Cut Integrating Texture Characterization for Interactive Image Segmentation

Cited by 10 publications

References 15 publications

Texture recognition based on diffusion in networks

Texture recognition based on diffusion in networks

Fusion Between Shape Prior and Graph Cut for Vehicle Image Segmentation

Application of an Improved Grab Cut Method in Tongue Image Segmentation

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