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In this paper, a visual servoing for the tracking of objects in a plane using a fixed camera system is shown. The method proposed of tracking makes use of a variable number of trackers determined automatically. The integration of the predictions of each of them affords a flexible and robust system of tracking. The studies of efficiency carried out reflect that the delays produced are suitable for use in visual servoing. The proposed system can be generalized to tracking three-dimensional objects with movable cameras.

In this paper, we present the results of the extension of the mathematical morphology to color images by treating multi-channel data as vectors. The approach presented here uses the HSI and related color spaces (intuitives). A modification of the lexicographical order for vectorial processing is developed. The importance of this new method lies on automatic selection of elements of the HSI and related color spaces to form an ordering structure. The achievement of the algorithm is realized through the introduction of a weight factor to reduce the high preference of the first component of the classic lexicographical order. Experimental results demonstrate the improvement of this new method.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper describes a vergence control algorithm for a 3D stereo recovery system. This work has been developed within framework of the project ROBTET. This project has the purpose of designing a Teleoperated Robotic System for live power lines maintenance. The tasks involved suppose the automatic calculation of path for standard tasks, collision detection to avoid electrical shocks, force feedback and accurate visual data, and the generation of collision free real paths. To accomplish these tasks the system needs an exact model of the environment that is acquired through an active stereoscopic head. A cooperative algorithm using vergence and stereo correlation is shown. The proposed system is carried out through an algorithm based on the phase correlation, trying to keep the vergence on the interest object. The sharp vergence changes produced by the variation of the interest objects are controlled through an estimation of the depth distance generated by a stereo correspondence system. In some elements of the scene, those aligned with the epipolar plane, large errors in the depth estimation as well as in the phase correlation, are produced. To minimize these errors a laser lighting system is used to help fixation, assuring an adequate vergence and depth extraction.

A fully integrated development tool for computer vision systems has been built in the framework of this paper. There are many applications that help the user in the design of such systems, using graphical interfaces and function libraries. Even in some cases, the final source code can be generated by these applications. This paper goes a step beyond; it allows the development of computer vision systems from a distributed environment. Besides, and as a distinctive characteristic with regard to other similar utilities, the system is able to automatically optimize task scheduling and assignment, depending on the available hardware.

Many inspection methods using computer vision have been developed, although in many of them the results obtained do not have the desired accuracy. In order to increase the system precision, two different solutions can be considered: the use of a more powerful image acquisition equipment and a solution that consists in developing algorithms that allow us to increase the accuracy of certain characteristics of the image. This paper is focused on setting a model that takes into account all the different signals involved in the image processing. It also defines the basis for the reconstruction of images in those areas with high content of information, such as edges, and more specifically those edges with a high change of intensity. In the image acquisition process, the input information is perfectly defined in a continuous domain and a discrete image is obtained as output, although distorted by the effects of the lenses, electrical sensor and the digitizer. This paper defines the conditions that the sampling process must satisfy in order to make possible the reconstruction of step edges using non-linear reconstruction filters in gray level images.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper presents a method for minimizing the total elapsed time spent by n tasks running on m differents processors working in parallel. The developed algorithm not only minimizes the total elapsed time but also reduces the idle time and waiting time of in-process tasks. This condition is very important in some applications of computer vision in which the time to finish the total process is particularly critical -- quality control in industrial inspection, real- time computer vision, guided robots. The scheduling algorithm is based on the use of two matrices, obtained from the precedence relationships between tasks, and the data obtained from the two matrices. The developed scheduling algorithm has been tested in one application of quality control using computer vision. The results obtained have been satisfactory in the application of different image processing algorithms.