Showing papers in "Pattern Recognition in 2004"

TL;DR: A framework to handle semantic scene classification, where a natural scene may contain multiple objects such that the scene can be described by multiple class labels, is presented and appears to generalize to other classification problems of the same nature.

TL;DR: This paper identifies some promising techniques for image retrieval according to standard principles and examines implementation procedures for each technique and discusses its advantages and disadvantages.

TL;DR: By applying an optimal pixel adjustment process to the stego-image obtained by the simple LSB substitution method, the image quality of the stega-image can be greatly improved with low extra computational complexity.

TL;DR: A new and definitive classification of patterns for structured light sensors is presented, based on projecting a light pattern and viewing the illuminated scene from one or more points of view, for recovering the surface of objects.

TL;DR: This tutorial performs a synthesis between the multiscale-decomposition-based image approach, the ARSIS concept, and a multisensor scheme based on wavelet decomposition, i.e. a multiresolution image fusion approach.

TL;DR: A large number of techniques to address the problem of text information extraction are classified and reviewed, benchmark data and performance evaluation are discussed, and promising directions for future research are pointed out.

TL;DR: This paper proposed a novel two factor authenticator based on iterated inner products between tokenised pseudo-random number and the user specific fingerprint feature, which generated from the integrated wavelet and Fourier–Mellin transform, and hence produce a set of user specific compact code that coined as BioHashing.

TL;DR: A cluster validity index and its fuzzification is described, which can provide a measure of goodness of clustering on different partitions of a data set, and results demonstrating the superiority of the PBM-index in appropriately determining the number of clusters are provided.

TL;DR: A review of the OCR work done on Indian language scripts and the scope of future work and further steps needed for Indian script OCR development is presented.

TL;DR: In this paper, the authors implemented the matrix multiplication of a neural network to enhance the time performance of a text detection system using an ATI RADEON 9700 PRO board, which produced a 20-fold performance enhancement.

TL;DR: The generalized projection function (GPF) is defined and it is shown that IPF, VPF, and HPF are all effective in eye detection, while HPF is better thanVPF, while VPF isbetter than IPF.

TL;DR: Results show that both gaits are potential biometrics, with running being more potent than walking, and a phase-weighted Fourier description gait signature by automated non-invasive means is derived.

TL;DR: An innovative watermarking scheme based on genetic algorithms (GA) in the transform domain is proposed, which is robust againstWatermarking attacks, and the improvement in watermarked image quality with GA.

TL;DR: It is argued that color and texture are separate phenomena that can, or even should, be treated individually.

TL;DR: A semi-automatic contour extraction method is used to address the problem of fuzzy tooth contours caused by the poor image quality, using the contours of the teeth as the feature for matching.

TL;DR: A comparison of normalization functions shows that moment-based functions outperform the dimension-based ones and the aspect ratio mapping is influential and the comparison of feature vectors shows that the improved feature extraction strategies outperform their baseline counterparts.

TL;DR: A new method for localizing and recognizing text in complex images and videos and showing good performance when integrated in a sports video annotation system and a video indexing system within the framework of two European projects is presented.

TL;DR: Integrative Co-occurrence matrices are introduced as novel features for color texture classification and the existence of intensity independent pure color patterns is demonstrated.

TL;DR: It is argued that feature selection is an important problem in object detection and demonstrated that genetic algorithms (GAs) provide a simple, general, and powerful framework for selecting good subsets of features, leading to improved detection rates.

TL;DR: An attempt to reflect shape information of the iris by analyzing local intensity variations of an iris image by constructing a set of one-dimensional intensity signals that reflect to a large extent their various spatial modes and are used as distinguishing features.

TL;DR: In this paper, a novel algorithm of incremental principal component analysis (PCA) is presented, which is computationally efficient for large-scale problems as well as adaptable to reflect the variable state of a dynamic system.

TL;DR: A new thresholding technique based on two-dimensional Renyi's entropy is presented, which extends a method due to Sahoo et al. (1997) and includes a previously proposed global thresholding methodDue to Abutaleb (Pattern Recognition 47 (1989) 22).

TL;DR: A new approach is developed, which allows the use of the k-means-type paradigm to efficiently cluster large data sets by using weighted dissimilarity measures for objects.

TL;DR: A new algorithm for determining the number of clusters in a given data set and a new validity index for measuring the "goodness" of clustering are presented.

TL;DR: The main characteristics of the proposed methods are image encryption, first stage compression-based frames differences and encryption of video whose compression error can be bounded pixelwise by a user specified value, very large number of encryption keys, and ability to encrypt large blocks of any digital data.

TL;DR: New algorithms that perform clustering and feature weighting simultaneously and in an unsupervised manner are introduced and can be used in the subsequent steps of a learning system to improve its learning behavior.

TL;DR: This paper presents a meta-modelling framework for selecting Informative Features with Fuzzy-Rough Sets and its application for Complex Systems Monitoring.

TL;DR: A new cluster validity index is proposed that determines the optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy c-means algorithm using an overlap measure and a separation measure between clusters.

TL;DR: Matching results on a database of 50 different fingers, with 200 impressions per finger, indicate that a systematic template selection procedure as presented here results in better performance than random template selection.

TL;DR: A novel algorithm for the automatic classification of low-resolution palmprints is proposed, using a set of directional line detectors to extract the principal lines of the palm in terms of their characteristics and their definitions in two steps.