A new image segmentation algorithm with applications to image inpainting

Silvia Ojeda, Ronny Vallejos and Oscar Bustos

Computational Statistics & Data Analysis, 2010, vol. 54, issue 9, 2082-2093

Abstract: This article describes a new approach to perform image segmentation. First an image is locally modeled using a spatial autoregressive model for the image intensity. Then the residual autoregressive image is computed. This resulting image possesses interesting texture features. The borders and edges are highlighted, suggesting that our algorithm can be used for border detection. Experimental results with real images are provided to verify how the algorithm works in practice. A robust version of our algorithm is also discussed, to be used when the original image is contaminated with additive outliers. A novel application in the context of image inpainting is also offered.

Keywords: Image; segmentation; Border; detection; Spatial; AR; models; Robust; estimators; Image; inpainting (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:54:y:2010:i:9:p:2082-2093

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