Recursive image sequence segmentation by hierarchical models

This paper addresses the problem of image sequence segmentation. A technique using a sequence model based on compound random fields is presented. This technique is recursive in the sense that frames are processed in the same cadency as they are produced. New regions appearing in the sequence are detected by a morphological procedure.Peer ReviewedPostprint (published version

Coagulation time detection by means of a real-time image processing

Several techniques for semi-automatic or automatic detection of coagulation time in blood or in plasma analysis are available in the literature. However, these techniques are either complex and demand for specialized equipment, or allow the analysis of very few samples in parallel. In this paper a new system based on computer vision is presented. An easy image processing algorithm has been developed, which leads to an accurate estimation of the coagulation time of several samples in parallel. The estimation can be performed in real time using transputer architecture supported by a PC.Peer ReviewedPostprint (published version

Prediction of image partitions using Fourier descriptors: application to segmentation-based coding schemes

This paper presents a prediction technique for partition sequences. It uses a region-by-region approach that consists of four steps: region parameterization, region prediction, region ordering, and partition creation. The time evolution of each region is divided into two types: regular motion and shape deformation. Both types of evolution are parameterized by means of the Fourier descriptors and they are separately predicted in the Fourier domain. The final predicted partition is built from the ordered combination of the predicted regions, using morphological tools. With this prediction technique, two different applications are addressed in the context of segmentation-based coding approaches. Noncausal partition prediction is applied to partition interpolation, and examples using complete partitions are presented. In turn, causal partition prediction is applied to partition extrapolation for coding purposes, and examples using complete partitions as well as sequences of binary images-shape information in video object planes (VOPs)-are presented.Peer ReviewedPostprint (published version

Image restoration using HOS and the Radon transform

The authors propose the use of higher-order statistics (HOS) to study the problem of image restoration. They consider images degraded by linear or zero phase blurring point spread functions (PSF) and additive Gaussian noise. The complexity associated with the combination of two-dimensional signal processing and higher-order statistics is reduced by means of the Radon transform. The projection at each angle is an one-dimensional signal that can be processed by any existing 1-D higher-order statistics-based method. They apply two methods that have proven to attain good one-dimensional signal reconstruction, especially in the presence of noise. After the ideal projections have been estimated, the inverse Radon transform gives the restored image. Simulation results are provided.Peer ReviewedPostprint (published version

Morphological detection based on size and contrast criteria. Application to cells detection

This paper deals with a detection algorithm relying on size and contrast criteria. It is suitable for a large range of applications where a priori information about the size and the contrast of the objects to detect is available. The detection is performed in three separate steps: the first one is a preprocessing which removes unuseful information with a size criterion. The second one performs a feature extraction based on contrast. Finally, the last step is the decision itself. All these steps make use of morphological transformations because of their ability to deal with the criteria of interest and of their low computational cost. As an example, this algorithm is applied to the automatic detection of spermatozoa.Peer ReviewedPostprint (published version

Segmentacion de imagenes mediante modelos de Gibbs-Markov

A coding oriented image segmentation algorithm is presented. This new method is based on Gibbs-Markov Random Fields (GMRF) for contourn information, a stationary gaussian model for region interna! information, and a preprocessing task for human visual system model. This is an extension of a previus work [4], which has been improved because the number of regions to be found is not fixed a priori. This fact gives better results, and is quite independent of the initial segmentation approach.Peer ReviewedPostprint (published version

Bit-slice implementation of a linear predictive vocoder

A digital 16-bit high-speed general-purpose signal-processor is shown. The main objective has been the implementation of a linear predictive vocoder for obtaining real-time speech compression. For real-time digital speech processing, fast devices and special procedure designs are needed. Thus, in obtaining high speed processors, multi-data paths, parallel and pipeline arquitectures have been adopted.Peer ReviewedPostprint (published version

Més enllà d’Atenea: un món per descobrir

La organització de l'activitat docent de l'assignatura Senyals i Sistemes, amb 4 hores de teoria a la setmana i 1 de laboratori, es fonamenta, d'una banda, en una proposta formal recollida a Atenea, i de l'altre en la interacció espontània entre alumnes i professor. Per que el procés d'interacció sigui de ràpida resposta, participatiu, àgil, adaptatiu, amb difusió extensa alhora que personalitzat i individualitzat, cal ampliar les prestacions d'Atenea. En aquest treball es presenten algunes opcions i es comenten els seus avantatges i inconvenients principals. Principalment la inclusió de formularis generats amb Google Docs, Google sites per presentar treballs de llarga durada i Dropbox com a repositori compartit. Aquests elements s'incorporen al curs mitjançant Atenea.Peer Reviewe

Temporal automatic edge detection of echocardiographic images

Peer ReviewedPostprint (published version