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Mathematical Methods in Pattern and image Analysis

作者： Sánchez-Garfias, F.A. Díaz-De-León S, J.L. Yáñez-Márquez, C. Pattern Recognition and Image Processing Laboratory Center for Computing Research I. P. N. 07738 Mexico D. F.

ISBN: (纸本)0819459216

This article introduces a new theoretical framework to describe the behavior of the Steinbuch's Lernmatrix. The properties of this old associative memory can be modeled using set theory and order relationships, analogously to morphological associative memories. The obtained results allow the Lernmatrix, four decades before its creation, to be a good alternative for pattern classification and recognition.

关键词： Matrix algebra

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FAST WATERSHED ALGORITHMS - ANALYSIS AND EXTENSIONS

FAST WATERSHED ALGORITHMS - ANALYSIS AND EXTENSIONS

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conference on Nonlinear image processing v

作者： DOBRIN, BP vIERO, T GABBOUJ, M TAMPERE UNIV TECHNOL SIGNAL PROC LABSF-33101 TAMPERE 10FINLAND

ISBN: (纸本)0819414751

Watershed transformation is used in morphological image segmentation. This transformation could be considered as a topographic region growing method. Recently, fast watershed algorithms have been proposed for general purpose computers. They are based on immersion simulations of the image surface, which is considered as a topographic relief. In such a model, the greylevel values of pixels stand for altitude values on the relief. In this paper, the operation of the present fast watershed algorithms is analyzed and a new extension is proposed. Drawbacks of the present algorithms are pointed out, studied, and illustrated with test images. These problems lead, in several cases, to a loss of information about image details and structures or even to unprocessed areas in the image. The new watershed algorithm overcomes these deficiencies and preserves more information about image details. The new algorithm is based on a split-and-merge scheme. It constantly monitors the presence of isolated areas during the immersion simulation, considering them as new catchment basins. Application of the split-and-merge watershed algorithm to marker-based image segmentation is discussed.

关键词： image processing algorithms and systems image segmentation image processing Nonlinear image processing Detection and tracking algorithms Floods Particles Raster graphics Computing systems Lead

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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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image Segmentation for Early Stage Brain Tumor Detection using Mathematical morphological Reconstruction 6

Image Segmentation for Early Stage Brain Tumor Detection usi...

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6th International conference on Smart Computing and Communications (ICSCC)

作者： Devkota, B. Alsadoon, Abeer Prasad, P. W. C. Singh, A. K. Elchouemi, A. Charles Sturt Univ Sch Comp & Math Sydney NSW Australia Natl Inst Technol Dept Comp Applicat Kurukshetra Haryana India Walden Univ Minneapolis MN USA

This study proposes a computer aided detection approach to diagnose brain tumor in its early stage using Mathematical morphological Reconstruction (MMR). image is pre-processed to remove noise and artefacts and then segmented to find regions of interest with probable tumor. A large number of textural and statistical features are extracted from the segmented image to classify whether the brain tumor in the image is benign or malignant. Experimental results show that the segmented images have a high accuracy while substantially reducing the computation time. The study shows that the proposed solution can be used to diagnose brain tumor in patients with a high success rate. (c) 2018 The Authors. Published by Elsevier B.v.

关键词： Brain Cancer Accuracy processing Time Segmentation

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Tools and Techniques for Annotating the Plant Leaf Diseases

Tools and Techniques for Annotating the Plant Leaf Diseases

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2022 OPJU International Technology conference on Emerging Technologies for Sustainable Development, OTCON 2022

作者： Praveen Gujjar, J. Naveen Kumar, v. Guru Prasad, M.S. Faculty of Management Studies Bengaluru India Dept. of Computer Science and Engg Dehradun India

ISBN: (纸本)9781665492942

Machine learning techniques and image processing plays significant role in identifying and classifying the leaf diseases. Classification is to classify the different leaf diseases based on different morphological characteristics. This paper focuses on the annotation tools such as *** and ***. Annotation refers to the process of identifying the regions in the image and then adding comments or metaphors on particular regions in the text format for the image. image annotation helps in assigning the keyword or the caption for the digital image. Further, this paper focused on identifying brown spot disease for paddy leaf and machine learning techniques for classification and stage of brown spot disease of paddy. The result shows that the *** and *** helps in image annotation. © 2023 IEEE.

关键词： image annotation

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Development of effective information-hiding method for embedded systems

Development of effective information-hiding method for embed...

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IEEE 56th International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Nakao, Kei Hozumi, Kohei Kumaki, Takeshi Ogura, Takeshi Fujino, Takeshi Ritsumeikan Univ Fac Sci & Engn 1-1-1 Nojihigashi Kusatsu Shiga Japan Ritsumeikan Univ Grad Sch Sci & Technol Shiga Japan

ISBN: (纸本)9781479900664

This paper reports on the JPEG compression tolerance of novel proposed digital watermarking algorithm that uses the morphological wavelet transform based on max-plus algebra. For objective evaluation, we investigated the image quality and tolerance against graphical data compression attack of an image during the digital-watermarking contest presented by the Committee for Information Hiding and its Criteria (IHC). During benchmarks of this contest, graphical data compression was done to reduce the file size of original image (45.5 MB) to 1/10 or less and the error rate of embedding data was reduced to 0%. As a result, the embedded data could be completely extracted. The peak signal-to-noise ratio (PSNR) was 54.08-54.66 dB. Afterwards, additional graphical data compression was done to reduce the file size to 1/20 or less of the original picture image and the error rate was reduced to 0%, and the PSNR was 52.75-54.35 dB. By compressing the image by, about 99%, the smallest data size attained was 0.49 MB and the PSNR was about 52 dB and maintained very high image quality with 0% of error rate. From these results, the processing time of the proposed algorithm was confirmed to be about 2.2 to 148.6 times faster than that of conventional algorithms on embedded systems.

关键词： image quality

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Iterative morphological algorithms for automated detection of landmines

Iterative morphological algorithms for automated detection o...

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conference on Detection and Remediation Technologies for Mines and Minelike Targets v

作者： Batman, S Goutsias, J Johns Hopkins Univ Ctr Imaging Sci Baltimore MD 21218 USA

ISBN: (纸本)081943664X

A new hybrid algorithm, based on combining the decorrelating and packing qualities of Principal Component (PC) analysis and the shape extracting and filtering properties of Mathematical Morphology, is investigated in the framework of land mine detection. The new method is similar in spirit to the MM-MNF algorithm, which is based on a linear pre-filter (the Maximum Noise Fraction (MNF) transform), followed by a morphological multispectral detection component (MM). The new filter (PC-MM), has a similar concatenated structure, and addresses some of the weaknesses inherent in the linear component of the MM-MNF algorithm;namely, the susceptibility of the MNF transform to clutter inhomogeneity, as well as to variations in clutter covariance estimation. The PC-MM algorithm addresses the stationarity problem by solely operating on image peaks extracted by a morphological top-hat transform. Therefore, the algorithm is much less susceptible to the presence of different textural regions. Subsequently, the peaks in the extracted multispectral top-hat image are projected into uncorrelated bands using the principal component (PC) transform. Due to the packing property of the PC transform, the target markers are typically found in the first and second bands in the PC transformed image (as opposed to any one or two of the 6 possible bands for the MNF transform). The targets a-re then detected using a variant of the morphological detection scheme (MM). The new method provides a fast and satisfactory first-pass detection result, for images of different clutter homogeneities and target types. The extracted tar-gets, from the first pass, are then used to improve the detection result in a subsequent iteration, by updating covariance estimates of relevant filter variables.

关键词： automatic mine detection mathematical morphology maximum noise fraction transform multispectral image processing and analysis

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ENHANCED AND SYNTHETIC vISION SYSTEMS DEvELOPMENT BASED ON INTEGRATED MODULAR AvIONICS FOR CIvIL AvIATION

ENHANCED AND SYNTHETIC VISION SYSTEMS DEVELOPMENT BASED ON I...

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IEEE/AIAA 32nd Digital Avionics Systems conference (DASC)

作者： vygolov, O. v. State Res Inst Aviat Syst Moscow Russia

ISBN: (纸本)9781479915361;9781479915385

The paper describes current results of a research and development (R&D) project aimed to create an advanced prototype of an Enhanced and Synthetic vision System (ESvS). The paper contains functional requirements for the ESvS prototype and discusses the main principles of its development. Brief overview of ESvS hardware and platform is given. The following image processing algorithms of ESvS are described: image enhancement based on modification of the Retinex algorithm, image fusion based on a morphological approach, runway detection based on the original modification of Hough transform - Projection Hough Transform, and runway obstacles detection based on photogrammetric method. The main features of the synthetic vision function of ESvS are described which provide computationally efficient creation of a realistic three-dimensional (3D) out-the-cabin view using terrain, objects, and texture databases.

关键词： Aerospace electronics Atmospheric modeling Databases Machine vision Prototypes Testing visualization

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Mathematical morphological filters and applications in seismic data denoising 81

Mathematical morphological filters and applications in seism...

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81st EAGE conference and Exhibition 2019

作者： Liu, Z. Wheaton, D. Tyagi, v. Wang, B. TGS

ISBN: (纸本)9789462822894

Mathematical morphological filtering (MMF) is a powerful tool for image processing based on the shape of the structure element (SE). It was introduced into seismic data processing to suppress noise and enhance signal quality. We explain the basic mathematic morphology concepts with set theory and define the basic and advanced morphological operations in seismic data processing. Unlike conventional seismic filtering techniques, MMF is a nonlinear operator so that it can more effectively isolate and attenuate seismic noise based on their shape differences from the signal. We apply different types of morphological filter on field (and various stages of processed) data to demonstrate their effectiveness for suppression of both coherent and incoherent noise and results in an improvement of signal to noise ratio. © 81st EAGE conference and Exhibition 2019. All rights reserved.

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Architectures of high-speed correlators with nonlinear and morphological image processing

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Proceedings of SPIE - The International Society for Optical Engineering 1994年 2321卷 538-541页

作者： Krasilenko, vladimir G. Motygin, vladimir v. Pastushenko, Alexander Polytechnical Inst. of Vinnitsa Vinnitsa Ukraine

ISBN: (纸本)0819416525

Making use of formulae transformation for calculation of linear and non-linear correlative functions and criterial functions of mean absolute error and mean square error, the authors show that these formulae can be reduced to two groups of mathematical constructions. These constructions determine two groups of architectures of parallel action: correlator with space (first group) and time (second group) multi-channel integration.

关键词： Optical correlation

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