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                    "codemeta:author": {
                        "codemeta:affiliation": "Yale University, USA",
                        "codemeta:name": "Pascal Getreuer"
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                    "codemeta:dateCreated": "2012-07-15",
                    "codemeta:datePublished": "2012-08-08",
                    "codemeta:description": "Chan-Vese Segmentation",
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                        "codemeta:identifier": "ISSN: 2105-1232 DOI: 10.5201/ipol",
                        "codemeta:name": "Image Processing On Line (IPOL)",
                        "codemeta:type": "Journal"
                    },
                    "codemeta:keywords": [
                        "image segmentation",
                        "level sets"
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                        "codemeta:abstract": "While many segmentation methods rely heavily in some way on edge detection, the \"Active Contours Without Edges\" method by Chan and Vese ignores edges completely. Instead, the method optimally fits a two-phase piecewise constant model to the given image. The segmentation boundary is represented implicitly with a level set function, which allows the segmentation to handle topological changes more easily than explicit snake methods.\nThis article describes the level set formulation of the Chan\u2013Vese model and its numerical solution using a semi-implicit gradient descent. We also discuss the Chan\u2013Sandberg\u2013Vese method, a straightforward extension of Chan\u2013Vese for vector-valued images.",
                        "codemeta:identifier": "https://doi.org/10.5201/ipol.2012.g-cv",
                        "codemeta:name": "Chan-Vese Segmentation",
                        "codemeta:url": "https://www.ipol.im/pub/art/2012/g-cv/article.pdf"
                    },
                    "codemeta:relatedLink": "http://demo.ipol.im/demo/g_chan_vese_segmentation/",
                    "codemeta:releaseNotes": "This code implements the Chan-Vese Segmentation Algorithm.",
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