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Title: Fast and accurate circle tracking using active contour models
Authors: Cuenca, Carmelo 
González, Esther 
Trujillo, Agustín 
Esclarín, Julio 
Mazorra, Luis 
Alvarez, Luis 
Martinez-Mera, Juan Antonio
Tahoces, Pablo G.
Carreira, José M.
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Keywords: Circle
Active Contour Models
Issue Date: 2018
Project: Nuevos Modelos Matemáticos Para la Segmentación y Clasificación en Imágenes 
Journal: Journal of Real-Time Image Processing 
Abstract: In this paper, we deal with the problem of circle tracking across an image sequence. We propose an active contour model based on a new energy. The center and radius of the circle is optimized in each frame by looking for local minima of such energy. The energy estimation does not require edge extraction, it uses the image convolution with a Gaussian kernel and its gradient which is computed using a GPU-CUDA implementation. We propose a Newton-Raphson type algorithm to estimate a local minimum of the energy. The combination of an active contour model which does not require edge detection and a GPU-CUDA implementation provides a fast and accurate method for circle tracking. We present some experimental results on synthetic data, on real images, and on medical images in the context of aorta vessel segmentation in computed tomography (CT) images.
ISSN: 1861-8200
DOI: 10.1007/s11554-015-0531-5
Source: Journal of Real-Time Image Processing[ISSN 1861-8200],v. 14, p. 793-802
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