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Détection et suivi d'objets par vision fondés sur segmentation par contour actif basé région

Wassima Ait Fares 1 
1 LAAS-RAP - Équipe Robotique, Action et Perception
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : Object segmentation and tracking is a challenging area of ongoing research in computer vision. One important application lies in robotics where the ability to accurately segment an object of interest from its background is crucial and particularly on images acquired onboard during robot motion. Object segmentation technique consists in separating the object region from the image background according to a pre-­‐defined criterion. Object tracking is a process of determining the positions of moving objects in image sequences. Several techniques can be applied to ensure these operations. In this thesis, we are interested to segment and track objects in video sequences using active contour method due to its robustness and efficiency to segment and track non-­‐rigid objects. Active contour method consists in making a curve converge from an initial position around the object to be detected towards this object boundary according to a pre-­‐defined criterion. We propose first a global criterion which depends on the image regions, what may impose certain constraints on the characteristics of these regions as a homogeneity assumption. This assumption may not always be verified due to the heterogeneity often present in images. In order to cope with the heterogeneity that may appear either in the object of interest or in the image background in noisy images using an inadequate active contour initialization, we propose a technique that combines local and global statistics in order to compute the segmentation criterion. By using a radius with a fixed size, a half-­‐disk is superposed on each point of the active contour to define the local extraction regions. However, when the heterogeneity appears on both the object of interest and the image background, we develop a new technique based on a flexible radius that defines two half-­‐disks with two different radius values to extract the local information. The choice of the value of these two radii is determined by taking into consideration the object size as well as the distance separating the object of interest from its neighbors. Finally, to track a mobile object within a video sequence using the active contour method, we develop a hybrid object tracking approach based on region characteristics and on motion vector of interest points extracted on the object region. Using our approach, the initial active contour for each image will be adequately adjusted in a way that it will be as close as possible to the actual boundary of the object of interest so that the evolution of active contour based on characteristics of the region will not be trapped by false contours. Simulation results on synthetic and real images validate the effectiveness of the proposed approaches.
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Submitted on : Thursday, January 16, 2014 - 3:39:46 PM
Last modification on : Tuesday, October 25, 2022 - 11:58:11 AM
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  • HAL Id : tel-00932263, version 1


Wassima Ait Fares. Détection et suivi d'objets par vision fondés sur segmentation par contour actif basé région. Automatique / Robotique. Université Paul Sabatier - Toulouse III, 2013. Français. ⟨NNT : ⟩. ⟨tel-00932263⟩



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