This paper examines the influence of head orientation in liptracking. There are two main conclusions: First, lip gesture analysis and head movement correction should be processed independently. Second, the measurement of articulatory parameters may be corrupted by head movement if it is performed directly at the pixel level. We thus propose an innovative technique of liptracking which relies on...

Parametric active contours have been widely used for image segmentation. However, high noise levels and weak edges are the most acute issues that hinder their performance, particularly in medical images. In order to overcome these issues, we propose an external force that weights the gradient vector flow (GVF) field and balloon forces according to local image features. We also propose a mechani...

We address the problem of updating road maps in dense urban areas by extracting the main road network from a very high resolution (VHR) satellite image. Our model of the region occupied by the road network in the image is innovative. It incorporates three different types of prior geometric knowledge: generic boundary smoothness constraints, equivalent to a standard active contour prior; knowled...

We present in this paper a new method to track moving objects. It is based on snakes or active contour models. We are concerned with football game analysis and so the moving objects tracked are representing football 'players. The camera is moving too. Our active contour algorithm does not need any preprocessing step contrary to most of the snake-based methods. It is based on classical energies ...

This paper presents a novel fast and robust model for active contours to detect objects in an image, based on techniques of curve evolution. The proposed model can detect objects whose boundaries are not necessarily defined by gradient, based on the minimization of a fuzzy energy. This fuzzy energy is used as the model motivation power evolving the active contour, which will stop on the desired...

This paper proposes a probabilistic prior-based active contour model for segmenting human brain MR images. Our model is formulated with the maximum a posterior (MAP) principle and implemented under the level set framework. Probabilistic atlas for the structure of interest, e.g., cortical gray matter or caudate nucleus, can be seamlessly integrate into the level set evolution procedure to provid...

An original method for an automatic detection of contours in difficult images is proposed. This method is based on a tight cooperation between a multi-resolution neural network and a hidden Markov model-enhanced dynamic programming procedure. This new method is able to overcome the three major drawbacks of the “standard” active contours: initialization dependancy, exclusive use of local informa...

This paper addresses a new segmentation model for texture image based on active contour and the model is driven by the simplified Cauchy-Schwarz divergence. First, we define a new texture descriptor with the Gauss curvature and the mean curvature of the textural region to represent the textural image space. Then, a novel active contour model has been developed to distinguish between object of i...

In the process of tree identification from pictures of leaves in a natural background, retrieving an accurate contour is a challenging and crucial issue. In this paper we introduce a method designed to deal with the obstacles raised by such complex images, for simple and lobed tree leaves. A first segmentation step based on a light polygonal leaf model is first performed, and later used to guid...

Microscopic image analysis is an essential process to enable the automatic enumeration and quantitative analysis of microbial images. There are several system are available for numerating microbial growth. Some of the existing method may be inefficient to accurately count the overlapped microorganisms. Therefore, in this paper we proposed an efficient method for automatic segmentation and count...