Enrique Rendón

Automatic car plate detection and recognition through intelligent vision engineering

License plate recognition systems are becoming the key to many traffic related applications such as road traffic monitoring or parking lot access control. In this paper, a software and hardware architecture implemented in the ESPRIT 5184 LOCOMOTIVE project for automatic vehicle plate number identification is presented. The system, developed in order to dynamically recognize symbol clusters on moving objects, integrates different computer vision techniques related to intrusion detection and automatic pattern recognition in slightly controlled environments, keeping real time operation.

Efficient image segmentation for region-based motion estimation and compensation

An intra-frame segmentation strategy to assist region-based motion estimation and compensation is presented. It is based on the multiresolution application of a histogram clustering and a probabilistic relaxation-labeling algorithm, followed by a local gradient-based bottom-up merging procedure. Specially suited for region-based video coding, it strongly differs from other proposals in that it generates arbitrary shaped image regions with pixel accuracy at a low computational cost, while allowing full reconstruction of the segmentation at the decoder without the transmission of any region description information.

Motorway surveillance through stereo computer vision

The demand for traffic monitoring systems is growing very quickly. The public transportation authorities have a clear need of these systems to gather as much traffic data as possible so that the proper solutions to congested road and motorways can be adopted. This paper presents a stereo computer vision system for traffic monitoring, developed within the European ESPRIT 8819 VICTORIA project. The system is based on stereo vision technology, which provides clear benefits and advantages with respect to conventional systems based on classical inductive loops or pneumatic tubes. Additionally, and compared to existing monocular vision based sensors, the VICTORIA system has the advantage of providing real world three dimensional information that allow vehicle classification. This is a requirement in some applications such as automatic tolling systems.

A monocular vision system for autonomous vehicle guidance

The improvement of vehicle security is a major priority of the car industry. Both active and passive security-systems have experienced a great development during the last decade, but the main research is still focused on minimising the errors committed by the driver rather than trying to avoid them. In this paper, a basic monocular vision system, focused on road location solely, is described. Working with only one video camera hinders the exact 3D reconstruction of the scene: no information about distances and dimensions is available, unless a priori artificial constraints are taken. The problem increases because of the movement of the camera with respect to the scene. In the present system, the road searching and following algorithms operate on the two-dimensional image plane, and 2D to 3D conversion is not accomplished. The system obtains excellent final results, succeeding in more than 75% of the analysed images from the tested sequences.

Contourless region-based video coding for very low bit-rates

In spite of their advantages, region-based approaches present a heavy burden in the required amount of information to describe region contours. To avoid these limitations, a new region-based motion estimation and compensation strategy is proposed, which allows the operation on arbitrary shaped regions and the ability to reconstruct them without any contour information. The strategy is enhanced by the use of multivector motion estimation and compensation. Results showing the quality and advantages of the strategy are provided.

Efficient prediction error regions determination for region-based video coding through shape adaptive DCT

An efficient strategy to determine the prediction error regions to be coded within a region-based prediction error coding scheme is presented. Prediction error coding is based on the segmentation of the displaced field difference (DFD) and coding the resulting arbitrary shaped DFD regions using shape adaptive DCT. Efficiency in the determination of the DFD regions to be coded is achieved by eliminating from the selection process the direct computation of the cost of region contours and textures coding. With this scheme, perceptual distortion of the decoded images is reduced while quality is locally improved on relevant image areas. Comparative results with the complete H.263 coder are shown.

Dynamic object segmentation for outdoor analysis

A new technique for dynamic object segmentation in outdoor environments is presented. It is based on an adaptive thresholding pixel-oriented strategy applied on a combination of static and dynamic differences that segments the motion presented in each image. A detection and tracking scheme helps reducing the processing areas to those in which the moving objects are present. Therefore, computational cost is highly reduced without any loss in the accuracy of the algorithm. Besides, shadows and occlusions (due to the perspective that is used) are detected and eliminated keeping similar computational savings. Results are shown on road traffic monitoring sequences.

Automatic antibiograms inhibition halo determination through texture and directional filtering analysis

A new segmentation and analysis strategy to automatically measure the inhibition halos (IHs) in antibiograms is presented. It is based on the application of a combined texture and directional filtering analysis technique on the result of a segmentation process which incorporates colour analysis and Hough transform applications. The computational efficiency is highly improved by applying the different processing stages to selected areas of the acquired images and exploiting a priori information about the IHs shape and distribution.

Region-based control points determination for multivector motion description

Motion description is a key clement in region-based video-coding approaches, becoming essential for low and very low bit-rate transmissions. Among the different advanced motion description approaches, multivector motion description (MMD) models the region motion through a variable number of motion vectors (MVs) applied on specific region points called control points (CPs). However, its application for region-based video coding would require the transmission of both MVs and CPs in order to adequately compensate each region motion. Here, a region-based control point determination strategy for MMD is proposed, which is strictly based on region contour information and the application of motion-interpolation accuracy constraints to drive the CPs location procedure. This approach offers two main advantages while keeping a reasonable computational cost: (1) it is able to operate on arbitrary-shaped regions of the image and (2) it allows the complete elimination of the transmission of any information related to the number and position of the CPs.

Determination of control point sets for motion description based on motion interpolation accuracy constraints

A region-based control point determination strategy for multivector motion description is proposed, which is strictly based on region contour information and the application of motion interpolation accuracy constraints to drive the location procedure. This approach gives two main advantages while keeping a reasonable computational cost: operation on arbitrary shaped regions of the image and the complete elimination of the transmission of any information related to the number and position of the control points.