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检索条件"任意字段=Conference on Image Algebra and Morphological Image Processing V"

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Structural analysis of artificial skin equivalents

Structural analysis of artificial skin equivalents

引用

conference on Optical Coherence Tomography and Coherence Techniques v

作者： Schmitt, Robert Marx, Ulrich Walles, Heike Schober, Lena Rhein Westfal TH Aachen Lab Machine Tools & Prod Engn WZL Steinbachstr 19 D-52074 Aachen Germany Fraunhofer Inst Prod Technol IPT D-52074 Aachen Germany Fraunhofer Inst Interfacial Engn & Biotechnol IGB D-70569 Stuttgart Germany

ISBN: (纸本)9780819486882

Artificial skin equivalents ASEs based on primary fibroblasts and keratinocytes show a high batch variance in their structural and morphological characteristics. Due to biological fluctuations and variable donor age, the growth processes of 3D tissue structure show a non constant quality. Since theses ASEs are used as testing system for chemicals, pharmaceuticals or cosmetics it is of major interest to know detailed and significant characteristics about each individual ASE. Until now, the microscopic analysis process is based on the destructive preparation of histologies allowing only the characterization on a random basis. In this study we present analytical methods to characterise each individual ASE by Optical Coherence Tomography OCT in combination with image processing tools. Therefore, we developed a fully automated OCT device, that performs automatic measurements of microtiter plates MTPs holing the ASEs in a sterile environment. We developed image processing algorithms to characterize the surface structure which may function as an indicator for defects in the epidermal stratum corneum. Further, we analysed the tomographic morphological structure of the ASEs. The results show, that variances in the growth state as well different collagen formation is detectable. In combination with dynamic threshold levels, we found, that OCT is a well suited technology for automatically characterizing artificial skin equivalents and may partly substitute the preparation of histologies.

关键词： Optical Coherence Tomography OCT Artificial Skin Equivalent ASE In vitro Monitoring Tissue Engineering Tissue Optics image processing

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Automatic segmentation of chromatographic images for region of interest delineation

Automatic segmentation of chromatographic images for region ...

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conference on Medical Imaging 2011 - image processing

作者： Mendonca, Ana M. Sousa, Antonio v. Sa-Miranda, M. Clara Campilho, Aurelio C. Univ Porto Inst Biomed Engn Rua Dr Roberto Frias S-N P-4200465 Oporto Portugal Univ Porto Fac Engn P-4200465 Porto Portugal Inst Politecn Porto Inst Super Engn P-4200487 Porto Portugal Inst Biol Mol & Celular P-4150180 Porto Portugal

ISBN: (纸本)9780819485045

This paper describes a segmentation method for automating the region of interest (ROI) delineation in chromatographic images, thus allowing the definition of the image area that contains the fundamental information for further processing while excluding the frame of the chromatographic plate that does not contain relevant data for disease identification. This is the first component of a screening tool for Fabry disease, which will be based on the automatic analysis of the chromatographic patterns extracted from the image ROI. image segmentation is performed in two phases, where each individual pixel is finally considered as frame or ROI. In the first phase, an unsupervised learning method is used for classifying image pixels into three classes: frame, ROI or unknown. In the second phase, distance features are used for deciding which class the unknown pixels belong to. The segmentation result is post-processed using a sequence of morphological operators in order to obtain the final ROI rectangular area. The proposed methodology was successfully evaluated in a dataset of 41 chromatographic images.

关键词： image segmentation Region of interest delineation Chromatographic images Fabry disease

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Genetic algorithm for features weighting and automatic parametrizing of the classification algorithm for graphemes

Genetic algorithm for features weighting and automatic param...

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2011 International conference on image processing, Computer vision, and Pattern Recognition, IPCv 2011

作者： Daher, H. Gaceb, D. Eglin, v. vincent, N. Bres, S. UMR 5205 CNRS INSA de Lyon 69621 Villeurbanne Cedex France Université René Descartes Systèmes Intelligents de Perception 75270 Paris Cedex France

ISBN: (纸本)9781601321916

We present in this paper a new mechanism for the clustering of graphemes that are issued from the decomposition of manuscripts. This clustering phase is important to simplify the automation of the analysis, the manuscripts transcription and the recognition of writers or styles. Our approach provides a feature weighting method by genetic algorithms and a high-performance methodology for the categorization of the shapes of graphemes by using graph coloring. We show how this coupling of these two mechanisms "weighting- classification" can offer a better separation of the forms to categorize by exploiting their grapho-morphological, their density and their significant orientations particularities.

关键词： Genetic algorithms

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A method to determine the size of the structuring element in morphological correction of non-uniform illumination

A method to determine the size of the structuring element in...

引用

IEEE International conference on image processing

作者： Juan v. Lorenzo-Ginori Faculty of Electrical Engineering Universidad Central Marta Abreu de Las Villas Cuba

Correction of uneven illumination in images is frequently used as a preprocessing step, for which morphological processing is a well established technique. This task has some specific characteristics for images containing disjoint blobs. These images appear frequently in applications like cellular imaging, where it is often necessary to process them in large amounts. In such cases, achieving a high degree of automation becomes an important factor. When correcting uneven illumination by morphological processing for this class of images, selecting an appropriate size for the structuring element (SE) is a relevant issue. In this work, a method based in grayscale morphological operations is presented, to determine an appropriate size of the SE. The effectiveness of the method was tested through simulations using images derived from real world examples. Results are presented in terms of tables showing the precision in recovering the original image intensities, as well as through illustrative images.

关键词： Lighting Gray-scale Transforms Microscopy image segmentation conferences

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Low-cost accurate skin detection using color and pseudo-morphological features

Low-cost accurate skin detection using color and pseudo-morp...

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IEEE International conference on Consumer Electronics (ICCE)

作者： S. Paschalakis A. Giani S. Hernandez-Marin Mitsubishi Electric Research and Development Centre Europe B. V. Guildford Surrey UK

This paper presents a new method for accurate skin detection. Skin detection techniques are used in various image and video processing applications, such as image categorization, face detection and tracking and, more recently, in selective image enhancement for digital Tv products. The proposed method achieves high accuracy using a combination of color information and pseudo-morphological processing, and is suitable for low-cost and custom hardware implementations.

关键词： Skin Pixel image color analysis Detectors Hardware Colored noise image resolution

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Recognition of electrical symbols in document images using morphology and geometric analysis

Recognition of electrical symbols in document images using m...

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International conference on image Information processing

作者： Paramita De Sekhar Mandal Partha Bhowmick Computer Science & Engineering Haldia Institute of Technology India Computer Science & Technology BESU Shibpur India Computer Science & Engineering IIT Kharagpur India

A robust and efficient algorithm for recognition of electrical symbols in digitized documents is proposed. The algorithm is based on morphological operations and geometric analysis to recognize different classes of symbols. Its novelty lies in building and usage of three spaces, namely H-, v -, and C-spaces, which respectively contain the horizontal line segments, the vertical line segments, and the circuit symbols present in the concerned drawing. These three spaces are built by morphological operations, which, in turn, are searched and scanned in a scientific way during the geometric analysis in order to obtain the recognized symbols by verifying the structural combination of their constituent primitives. Exhaustive experimentation has been performed to test the performance of the algorithm. Some of the results are presented in this paper to demonstrate its robustness, efficiency, and versatility.

关键词： image segmentation Logic gates Information processing Algorithm design and analysis Shape image edge detection FETs

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SINGLE-FRAME-BASED RAIN REMOvAL vIA image DECOMPOSITION

SINGLE-FRAME-BASED RAIN REMOVAL VIA IMAGE DECOMPOSITION

引用

IEEE International conference on Acoustics, Speech and Signal processing

作者： Yu-Hsiang Fu Li-Wei Kang Chia-Wen Lin Chiou-Ting Hsu Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9781457705380

Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image has been rarely studied in the literature, where no temporal information among successive images can be exploited, making it more challenging. In this paper, to the best of our knowledge, we are among the first to propose a single-frame-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis (MCA). Instead of directly applying conventional image decomposition technique, we first decompose an image into the low-frequency and high-frequency parts using a bilateral filter. The high-frequency part is then decomposed into "rain component" and "non-rain component" via performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.

关键词： Rain removal sparse coding dictionary learning image decomposition morphological component analysis (MCA) images rain imagery (Psychotherapy) image decomposition Sparse coding time information decomposition original image High frequency videotapes image

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A new 3D paradigm for metal artifact reduction in dental CT

A new 3D paradigm for metal artifact reduction in dental CT

引用

IEEE International conference on image processing

作者： v. Naranjo R. Lloréns M. Alcañiz R. verdú-Monedero J. Larrey-Ruiz J. Morales-Sánchez I3BH Universidad Politécnica de Valencia Valencia Spain Uiversidad Politécnica de Cartagena Cartagena Spain

The presence of metal artifacts in dental CT prevents the correct exploration and planning of dental interventions. This paper addresses a new paradigm in metal artifact reduction that uses the backprojected data available in the DICOM files. The method, based on variational image registration and morphological lambda reconstruction, enhances the image quality using not only the information of the artifacted image (horizontal approach) but also the information of adjoining images (vertical approach). Some preliminary results involving different CT scanners and patients are presented and discussed.

关键词： Computed tomography Metals Dentistry image registration Three dimensional displays image reconstruction image restoration

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AN UNSUPERvISED ALGORITHM FOR HYBRID/morphological SIGNAL DECOMPOSITION

AN UNSUPERVISED ALGORITHM FOR HYBRID/MORPHOLOGICAL SIGNAL DE...

引用

IEEE International conference on Acoustics, Speech and Signal processing

作者： Matthieu Kowalski Thomas Rodet Laboratoire des Signaux et SystemesUMR 8506 CNRS-SUPELEC-Univ. Paris-Sud91172 Gif-sur-Yvette Cedex

ISBN: (纸本)9781457705380

The main contribution presented here is an adaptive/unsupervised iterative thresholding algorithm for sparse representation of signals which can be modeled as the sum of two components. Such Hybrid or morphological representations are known to be well adapted for applications in image or audio signal processing. The proposed algorithm uses a Bernoulli-Gaussian prior on the synthesis coefficients of the signal, with morphological depending parameters. Using an EM-framework introduced by Figueiredo and Nowak in the case of the convex l_(1) prior, we derive an unsupervised algorithm in the spirit of ISTA, with iteratively adapted thresholding/shrinkage.

关键词： Sparse representation Adaptive Thresholding Hybrid model morphological Component Analysis sparse representation algorithms signals audio signal processing WWOX gene imagery (Psychotherapy) images audio signals TWO-COMPONENT Spirits

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Prominent Boundaries and Foreground Detection Based Technique for Human Face Extraction from Color images Containing Complex Background

Prominent Boundaries and Foreground Detection Based Techniqu...

引用

National conference on Computer vision, Pattern Recognition, image processing and Graphics (NCvPRIPG)

作者： Darshak G. Thakore A.I. Trivedi Computer Engineering B V M Engineering College Vallabh Vidyanagar India Faculty of Technology & Engineering MS university Vadodara India

The paper proposes a novel method for human face extraction from color images, characterized by uncontrolled illumination conditions and complex backgrounds. The method incorporates stationary Haar wavelet transform & proximity influence for prominent boundaries detection and watershed transform, proximity influence & morphological operations to separate foreground / background along with region and color attributes for human face extraction. The method exploits redundancy by coalescing local color cues of all color channels to emphasize reliable processing to precisely detect the human face by avoiding under-segmentation and reducing over-segmentation & artifacts. The method has been tested on face-image collection of standard database and on images captured by an amateur photographer for various complex backgrounds having diversified textures, varied illumination conditions and multiple background objects. The presented results show the effectiveness of the method for human face extraction, proving it suitable as an input to applications like digital album catalogue, content based image retrieval, face recognition and facial expression recognition.

关键词： Face image segmentation image color analysis Lighting Discrete wavelet transforms Humans

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