COVERED DISTANCES OF HANDBALL PLAYERS OBTAINED BY AN AUTOMATIC TRACKING METHOD

The aim of this work is to obtain the distances covered by handball players and their velocities during a match using a new approach based on automatic tracking method described in Figueroa et. al. (2006a, 2006b) and the Adaboost detector (Okuma, 2004). A whole game of a Brazilian regional handball championship for players under age of 21 was recorded. Applying the mentioned automatic tracking, the accumulated covered distances and the velocities were calculated for all the players. The results of average covered distances (±SD) in the 1st and 2 nd halves were 2199(±230) and 2453(±214). The results of covered distances and the velocities allow individual and collective analyses of the players by the team staff. The proposed method revealed to be a powerful tool to improve physical analysis of the handball players

Simd Parallel Algorithm For Classifying Binary Image Contours Based On Mathematical Morphology

In this paper we analyze some problems concerned with connectivity on binary images. More precisely, by means of Mathematical Morphology we describe an algorithm which detects and classifies contours of connected sets as inner or outer contours. The method discussed here is quite parallel and can be directly implemented onto an SIMD (Single-instruction Multiple-data-stream) massively parallel computer.3252

Morphological Residues and a General Framework for Image Filtering and Segmentation

Morphological residues represent an image in an hierarchical way by means of a decomposition of its structures and according to a size parameter . From this decomposition, we can obtain a relation between the different residual levels associated with the complexity of the image structures. In this work, we introduce a new method to filter out components of gray-scale images based on the morphological residue decomposition which takes into account a size parameter and a certain level of complexity of the different structures to be filtered. As we will illustrate, this complexity is associated with a set of new attributes of the image defined according to the information contained in its multi-resolution representation.</p

Morphological Residues and a General Framework for Image Filtering and Segmentation

Morphological residues represent an image in an hierarchical way by means of a decomposition of its structures and according to a size parameter λ. From this decomposition, we can obtain a relation between the different residual levels associated with the complexity of the image structures. In this work, we introduce a new method to filter out components of gray-scale images based on the morphological residue decomposition which takes into account a size parameter and a certain level of complexity of the different structures to be filtered. As we will illustrate, this complexity is associated with a set of new attributes of the image defined according to the information contained in its multi-resolution representation

Segmentation Of Nautical Chart Components Using Mathematical Morphology

This paper presents some procedures for segmenting nautical charts using concepts of mathematical morphology. The method, discussed here, based on the multi-angled parallelism, is capable of extracting overlapped connected components such as lakes, isolines, railways, canals, small symbols and strings of characters. The problem of connectivity is solved using geodesic operations. The procedures have been applied to a 1/50000 scale nautical chart of the Brazilian navy scanned at a resolution of 300 dpi.3535

A Flexible Software For Tracking Of Markers Used In Human Motion Analysis.

In this work, we present a software for the tracking of markers used in human motion analysis. This software is based mainly on image sequences captured by video cameras and on image processing and computer vision tools. Unlike the optoelectronic systems, which record only the coordinates of the markers, a video-based system offers more visual information and flexibility which can be exploited in different applications. However, it needs a more complex tracking procedure concerned with the extraction and identification of the used markers. The tracking module presented here is divided into the following three procedures: segmentation, matching and prediction. The segmentation consists in extracting the objects of interest (markers). The matching is used to find the correspondence between the extracted objects in two consecutive frames. The prediction is important to limit the region of processing, thus reducing the execution time. Some results of the automatic tracking are presented together with their application in human motions analysis.72155-6

Wavelet-based Feature Extraction for Fingerprint Image Retrieval

This paper presents a novel approach to fingerprint retrieval for personal identification by joining three image retrieval tasks, namely, feature extraction, similarity measurement, and feature indexing, into a wavelet-based fingerprint retrieval system. We propose the use of different types of Wavelets for representing and describing the textural information present in fingerprint images. For that purposes, the feature vectors used to characterize the fingerprints are obtained by computing the mean and the standard deviation of the decomposed images in the Wavelet domain. These feature vectors are used to retrieve the most similar fingerprints given a query image, while their indexation is used to reduce the search spaces of image candidates. The different types of Wavelets used in our study include: Gabor Wavelets (GWs), Tree-Structured Wavelet Decomposition using both Orthogonal Filter Banks (TOWT) and Bi-orthogonal Filter Banks (TBOWT), as well as the Steerable Wavelets. To evaluate the retrieval accuracy of the proposed approach, a total number of eight different data sets were used. Experiments also evaluated different combinations of Wavelets with six similarity measures. The results show that the Gabor Wavelets combined with the Square Chord similarity measure achieves the best retrieval effectiveness.