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International conference on Pattern Recognition

作者： A.L. Bogush A.v. Tuzikov S.A. Sheynin United Institute of Informatics Problem National Academy of Science of Belarus Minsk Belarus National Center of Informational Resources and Technologies National Academy of Science of Belarus Minsk Belarus

We propose a 3D object reconstruction algorithm from non-parallel object cross-sections. The algorithm is based on two-dimensional morphological morphing, affine transform and cubic spline interpolation. The algorithm... 详细信息

关键词： Interpolation Ultrasonic imaging image reconstruction Shape Spline Probes Informatics Reconstruction algorithms image processing image sensors

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Color image compression/reconstruction by YUv fuzzy wavelets

Color image compression/reconstruction by YUV fuzzy wavelets

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conference of the North American Fuzzy Information processing Society - NAFIPS

作者： H. Nobuhara K. Hirota Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Yokohama Japan

A color image compression/reconstruction method based on fuzzy wavelets is proposed, where YUv color space is employed. Since the Y space includes more important information than that of U and v space, more efficient image compression/reconstruction can be achieved compared with RGB space based one by employing the condition that the file-size of compressed image of Y space is bigger than that of U and v space. The proposed YUv fuzzy wavelets are based on a partial fuzzification of morphological wavelets, and the operations of the wavelets can be performed by fuzzy relational calculus, partially. To compress/reconstruct the image effectively, a soft threshold scheme can be given as alpha-band, which is an extended concept of, alpha-cut of fuzzy relation. Through an experiment using a color image extracted from SIDBA, it is confirmed that the root mean square error of the proposed YUv fuzzy wavelets is decreased to 78.65% of that of RGB fuzzy wavelets, under the condition that the compression rate is about 0.11.

关键词： Color image coding image reconstruction Space technology Signal analysis Calculus Signal synthesis Fuzzy systems Computational intelligence Wavelet analysis

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morphological classification of blood leucocytes by microscope images

Morphological classification of blood leucocytes by microsco...

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IEEE International conference on Computational Intelligence for Measurement Systems and Applications (CIMSA)

作者： v. Piuri F. Scotti Department of Information Technologies University of Milan Crema Italy

The classification and the count of white blood cells in microscopy images allows the in vivo assessment of a wide range of important hematic pathologies (i.e., from presence of infections to leukemia). Nowadays, the morphological cell classification is typically made by experienced operators. Such a procedure presents undesirable drawbacks: slowness and it presents a not standardized accuracy since it depends on the operator's capabilities and tiredness. Only few attempts of partial/full automated systems based on image-processing systems are present in literature and they are still at prototype stage. This paper presents a methodology to achieve an automated detection and classification of leucocytes by microscope color images. The proposed system firstly individuates in the blood image the leucocytes from the others blood cells, then it extracts morphological indexes and finally it classifies the leucocytes by a neural classifier in Basophil, Eosinophil, Lymphocyte, Monocyte and Neutrophil.

关键词： White blood cells Microscopy Cells (biology) Pathology image analysis Performance analysis Morphology Information technology In vivo Prototypes

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Object color propagation in an unregistered distributed video sensor network

Object color propagation in an unregistered distributed vide...

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IEEE International conference on image processing

作者： v. venkataraman S. Srinivasan A. Stefanidis Department of Spatial Information Science and Engineering Analysis University of Maine Orono ME USA

In this paper we address the use of object color characteristics as a predominant linking parameter between disjoint video scenes in unregistered distributed video sensor networks. In our approach we proceed by tracking objects in high-resolution video scenes using accumulated frame differencing and morphological techniques. We continue by minimizing shadow effects in object tracking through background detection, in order to obtain more accurate object color signatures. These signatures are then used to link trajectory fragments across disjoint video feeds in a sensor network. We present experimental results to demonstrate the performance of our approach, especially addressing the effect of resolution in tracking, and the role of color signatures as a key linking element when video scene registration is not possible.

关键词： Intelligent networks Layout Feeds Optical sensors Cameras Object detection Tracking Joining processes Temperature sensors Motion analysis

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Design of an Automated‐Counting System of Cell Micronuclei in Micrographs

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AIP conference Proceedings 2004年第1期724卷 124-127页

作者： A. v. Lozano J. A. Márquez A. E. Buenfil M. E. Gonsebatt 1Centro de Ciencias Aplicadas y Desarrollo Tecnológico PO Box 70‐186 México 04510 UNAM 2Instituto de Física UNAM 3Instituto de Investigaciones Biomédicas UNAM

We developed and tested a system for the automatic analysis of cell images in order to identify and count micronuclei configurations in digital images from a microscope. The presence of micronuclei has been used as an indicator of DNA damage, and a fast automated analysis may be suitable for early cancer detection, for example. We describe in this work the image‐processing protocol and system comprising: acquisition, color normalization, contrast enhancement, color‐background removing, color segmentation, mathematical‐morphology filtering and restoration, morphometry, feature extraction and analysis, and counting. Among the morphological features used for discriminating micronuclei configurations, we tested compactness, area ratios and separation of selected features (ideally, a nucleus and one or more micronuclei). Among the mathematical‐morphology techniques, we used for instance a modified watershed segmentation algorithm for separating touching features. We present our results on several images, the evaluation and performance of each step, and the main problems we solved by using several techniques from mathematical morphology and color‐image processing.

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Associative morphological memories for endmember determination in spectral unmixing

Associative morphological memories for endmember determinati...

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12th IEEE International conference on Fuzzy Systems

作者： Graña, M Sussner, P Ritter, G Univ Basque Country Dept CCIA San Sebastian Spain

ISBN: (纸本)0780378105

Autoassociative morphological Memories (AMM) are a construct similar to Hopfield Autoassociative Memories defined on the (R, +, v, A) lattice algebra. Unlimited storage and perfect recall of noiseless real valued patterns has been proved for AMM's. However AMM's suffer from sensitivity to specific noise models, that can be characterized as erosive and dilative noise. On the other hand, Spectral Unmixing of Hyperspectral images needs the prior definition of a set of Endmembers, which correspond to material spectra lying on vertices of the minimum convex region covering the image data. These vertices can be characterized as morphologically independent patterns. We present a procedure based on the AMM noise sensitivity for Endmember detection based on this characterization.

关键词： image processing

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Kernel computation in morphological associative memories for grayscale image recollection

Kernel computation in morphological associative memories for...

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Proceedings of the Fifth IASTED International conference on Signal and image processing

作者： Urcid, Gonzalo Ritter, Gerhard X. Optics Department INAOE Tonantzintla Pue. 72000 Mexico CISE Department University of Florida Gainesville FL 32611 United States

ISBN: (纸本)0889863784

morphological associative memories (MAMs) form a subclass of morphological neural networks. Storage and recall in MAMs is realized using the matrix numerical operations of minimax algebra in a similar fashion as the classic correlation encoding technique. The kernel method, based upon strong morphological independence of the exemplar pattern set, allows to combine two MAMs for enhancing the recall capability when dealing with non-boolean patterns corrupted by random uniform noise. This paper describes a new procedure for assigning a kernel to any set of exemplar patterns that are restricted to have non-negative entries over a finite set of values. Thus, our attention is focused to the specific case of grayscale images and we show, by means of illustrative examples, the recollection capability of the kernel based morphological associative memory scheme including a probabilistic model for its performance.

关键词： Neural networks

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Towards automatic redeye effect removal

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PATTERN RECOGNITION LETTERS 2003年第11期24卷 1767-1785页

作者： Smolka, B Czubin, K Hardeberg, JY Plataniotis, KN Szczepanski, M Wojciechowski, K Silesian Tech Univ Dept Automat Control Elect & Comp Sci PL-44101 Gliwice Poland Univ Toronto Edward S Rogers Sr Dept ECE Toronto ON M5S 3G4 Canada Gjovik Univ Coll N-2802 Gjovik Norway

The redeye effect is typically formed in amateur photographs taken with a built-in camera flash. Analysis of the available techniques and products indicates that their efficiency in correcting this artifact is limited and their performance is inconsistent. In this work we propose a user friendly solution, which could be used to restore amateur photographs. In the proposed method the redeye effect is detected using a skin detection module and eye colors are restored using morphological image processing. The new method is computationally efficient, robust to parameter settings and versatile, as it can work in conjunction with a number of skin detection methods. (C) 2002 Elsevier Science B.v. All rights reserved.

关键词： redeye removal skin detection restoration color image enhancement

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image segmentation and restoration using inverse diffusion equations and mathematical morphology

Image segmentation and restoration using inverse diffusion e...

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conference on SAR image Analysis, Modeling and Techniques v

作者： Dong, NL Jin, G Chen, HB Ma, JG Qi, B Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Sichuan Peoples R China

ISBN: (纸本)0819446653

Segmentation and restoration of highly noisy images is a very challenging problem. There are a number of methods reported in the literature, but more effort still need to be put on this problem. In this paper we describe the development and implementation of a new effective approach to segmentation and restoration of imagery with pervasive, large amplitude noise. The new approach is based on the recently developed stabilized inverse diffusion equations (SIDE) and mathematical morphology. First, we find an optimized SIDE force function. Secondly, we segment the image to several regions accurately using the SIDE method. Finally a grayscale, mathematical morphological filter combined with SIDE is assigned to, the initial image data in each region to suppress the noise and to restore the total image. A test study based on available database is presented, and the results so far indicate that this approach to highly noisy imagery segmentation and restoration is highly effective.

关键词： diffusion segmentation restoration mathematical morphology image processing

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Rule-driven defect detection in CT images of hardwood logs

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2003年第1-3期41卷 101-119页

作者： Sarigul, E Abbott, AL Schmoldt, DL Virginia Tech Bradley Dept Elect & Comp Engn Blacksburg VA 24061 USA Univ Wisconsin USDA US Forest Serv Dept Biol Syst Engn Madison WI 53706 USA

This paper deals with automated detection and identification of internal defects in hardwood logs using computed tomography (CT) images. We have developed a system that employs artificial neural networks (ANNs) to perform tentative classification of logs on a pixel-by-pixel basis. This approach achieves a high level of classification accuracy for several hardwood species (northern red oak, Quercus rubra, L., water oak, Q. nigra, L., yellow poplar, Liriodendron tulipifera, L., and black cherry, Prunus serotina, Ehrh.), and three common defect types (knots, splits, and decay). Although the results are very satisfactory statistically, a subjective examination reveals situations that could be refined in a subsequent post-processing step. We are currently developing a rule-based, contextual approach to region refinement that augments the initial emphasis on local information. The resulting rules are domain dependent, utilizing information that depends on region shape and type of defect. For example splits tend to be long and narrow, and this knowledge can be used to merge smaller, disjoint regions that have tentatively been labeled as splits. Similarly, image regions that represent knots, decay, and clear wood can be refined by removing small, spurious regions and by smoothing the boundaries of these regions. Mathematical morphology operators can be used for most of these tasks. This paper provides details concerning the domain-dependent rules by which morphology operators are chosen, and for merging results from different operations. (C) 2003 Elsevier Science B.v. All rights reserved.

关键词： rule-based analysis morphological image processing defect detection wood processing

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