Showing papers in "Pattern Recognition in 2001"

TL;DR: This survey provides a summary of color image segmentation techniques available now based on monochrome segmentation approaches operating in different color spaces and some novel approaches such as fuzzy method and physics-based method are investigated.

TL;DR: However, for a task with very high dimensional data such as images, the traditional LDA algorithm encounters several difficulties, and before LDA can be used to reduce dimensionality, another procedure has to be first applied for dimensionality reduction.

TL;DR: In this article, a simple rule for adapting the class combiner to the application is presented, where decision templates (one per class) are estimated with the same training set that is used for the set of classifiers.

TL;DR: A novel method to embed important data in the host image so that the interceptors will not notice about the existence of the data is developed and an improved hiding technique is developed to obtain a high-quality embedding result.

TL;DR: It is shown that defining edges in this manner causes some obvious edges to be missed and how to revise the Canny edge detector to improve its detection accuracy is shown.

TL;DR: By extracting uncorrelated discriminant features, face recognition could be performed with higher accuracy on lower than 16×16 resolution mosaic images and it is suggested that the optimal face image resolution can be regarded as the resolution m × n which makes the dimensionality N = mn of the original image vector space be larger and closer to the number of known-face classes.

TL;DR: The least-squares fitting minimizes the squares sum of error-of-fit in predefined measures by the geometric fitting of circle/sphere/ellipse/hyperbola/parabola and simple and robust nonparametric algorithms are proposed.

TL;DR: The DCS method proposed is based on the concepts of “classifier’s local accuracy” (CLA) and MCB and exploits the concept of MCB for DCS purposes, while the BKS method is aimed at classifier combination.

TL;DR: Experimental results demonstrate that the proposed HMM approach yields a satisfactory and higher recognition rate for user images of different hand size, shape and skew angle.

TL;DR: J-M eans outperforms the other local search methods, quite substantially when many entities and clusters are considered, and fits into the variable neighborhood search metaheuristic framework.

TL;DR: This paper proposes to use signed gray-level di!erences and their multidimensional distributions for texture description and shows that this approach provides a very good and robust performance in comparison with the mainstream paradigms such as cooccurrence matrices, Gaussian Markov random "elds, or Gabor ltering.

TL;DR: It is shown that by decomposing a face image using wavelet transform, the low-frequency face image is less sensitive to the facial expression variations and it is proved that the spectroface representation is invariant to translation, scale and on-the-plane rotation.

TL;DR: A genetic algorithm is proposed for clustering the data with compact spherical clusters that can be used in two ways, the user-controlled and an automatic clustering, where a heuristic strategy is applied to find a good clustering.

TL;DR: A number of evolutionary agents are uniformly distributed in the 2-D image environment to detect the skin-like pixels and segment each face-like region by activating their evolutionary behaviors, and wavelet decomposition is applied to each region to detect possible facial features.

TL;DR: A novel eye detection method for gray intensity image that uses multi-cues for detecting eye windows from a face image using variance projection function for eye detection and verification.

TL;DR: An efficient algorithm for human face detection and facial feature extraction is devised using the genetic algorithm and the eigenface technique, and the lighting effect and orientation of the faces are considered and solved.

TL;DR: A novel definition of histogram capacity curve taking into account the density distribution of histograms in the corresponding spaces is proposed and used to quantify the effectiveness of image descriptors and histogram dissimilarities in image retrieval applications.

TL;DR: A new methodology which performs both lossless compression and encryption of binary and gray-scale images, based on SCAN patterns generated by the SCAN methodology is presented.

TL;DR: A holistic system for the recognition of handwritten Farsi/Arabic words using right–left discrete hidden Markov models (HMM) and Kohonen self-organizing vector quantization is presented.

TL;DR: A threshold FFT approach is developed to simultaneously smooth and enhance poor quality images derived from a database of imperfect prints using a novel wedge ring overlay minutia detector that is particularly robust to imperfections.

TL;DR: In this paper, prototype learning is used to improve the classification performance of nearest-neighbor (NN) classifier and reduce the storage and computation requirements of NN classifier.

TL;DR: A minutiae detection procedure based on adaptive tracing the gray-level ridge of the fingerprint image with piecewise linear lines of different length is presented, which will greatly reduce the computational time.

TL;DR: A template-based system for online character recognition where the number of representative templates is determined automatically where these templates can be viewed as representing different styles of writing a particular character.

TL;DR: A multiresolution approach for the inspection of local defects embedded in homogeneous textured surfaces is presented and a simple thresholding can be used to discriminate between defective regions and homogeneous regions in the reconstructed image.

TL;DR: A linear constrained distance-based discriminant analysis (LCDA) that uses a criterion for optimality derived from Fisher's ratio criterion that maximizes the ratio of inter-distance between classes to intra-distance within classes but also imposes a constraint that all class centers must be aligned along predetermined directions.

TL;DR: A rule-based heuristic merging technique to reduce the over-segmentation of cells is proposed based on some heuristic rules and gives more than 90% accurate segmentation when compared to simple classical watershed extended to 3-D.

TL;DR: This paper considers two well-founded PDE methods: a nonlinear isotropic diffusion filter that permits edge enhancement, and a convex nonquadratic variational image restoration method which gives good denoising.

TL;DR: An Arabic OCR system is proposed, which uses a recognition-based segmentation technique to overcome the classical segmentation problems and shows a 90% recognition accuracy with a 20 chars/s recognition rate.

TL;DR: Two methods of eye detection in a face image are described: the face is first detected as a large flesh-colored region, and anthropometric data are then used to estimate the size and separation of the eyes.

TL;DR: This method is able to obtain reliable stroke correspondence and enable structural interpretation and some structural post-processing operations are applied to improve the stroke correspondence.