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检索条件"任意字段=Intelligent Robots and Computer Vision IX: Algorithms and Techniques"

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ESTABLISHING IDENTITY AND POSE OF OBJECTS FROM A LIBRARY USING RECIPROCAL BASIS-SET AND DIRECTION-OF-ARRIVAL techniques 12

ESTABLISHING IDENTITY AND POSE OF OBJECTS FROM A LIBRARY USI...

引用

12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： WRIGHT, CR VAZ, RF CYGANSKI, D WORCESTER POLYTECH INST DEPT ELECT & COMP ENGNMACHINE VIS LABWORCESTERMA 01609

ISBN: (纸本)0819413208

In many object recognition problems, the object to be identified is one of a fixed set (library) of objects. The problem of identifying which object is present then shares characteristics of the signal detection and parameter estimation problem: which signal is present and what are its parameters? The Reciprocal Basis Set/Direction of Arrival (RBS/DOA) technique is a recently developed technique for object pose determination. It uses a single, comprehensive analytic object model representing a suite of views of an object. Object orientation can be directly established from single 2-D views of the object, without a costly search of the pose parameter space, and without need for the views to be related by a geometric image transformation. This paper describes how one can construct reciprocal basis sets to simultaneously determine object identity and pose from a single 2-D image. Results are presented which demonstrate this ability for a single unknown pose parameter using synthetic and camera-acquired images.

关键词： Visual process modeling Machine vision computer vision technology Robot vision robots Wavefronts Error analysis Image processing Object recognition Signal detection

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IMAGE-CODING AND IMAGE ACTIVITY MEASUREMENT 12

IMAGE-CODING AND IMAGE ACTIVITY MEASUREMENT

引用

12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： KEISSARIAN, F IBRAHIM, MK DAEMI, MF UNIV NOTTINGHAM DEPT COMP SCIRECOGNIT ENGN GRPNOTTINGHAM NG7 2RDENGLAND

ISBN: (纸本)0819413208

In this paper, a novel image analysis technique is proposed, which may be performed prior to coding in order to decide what is the most significant information to encode. In the proposed system, the image to be coded is first partitioned into a large number of sub-blocks of N*N pixels. The blocks can then be stored into two major classes according to the level of the visual activity present. The classification is based on analyzing the local histogram within each sub-block. In this paper, we initially analyze the image blocks to separate uniform blocks from those that can be classified as non-uniform blocks. Adjacent uniform blocks with the same statistics are merged to form large blocks. These blocks can then be coded by their mean values. It is also shown that the non-uniform blocks may also be classified into three categories with different levels of activity.

关键词： Image compression Image quality Image analysis computer vision technology Machine vision Robot vision robots Image processing Statistical analysis Image transmission

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WAVELET TRANSFORM IN-DEPTH RECOVERY 12

WAVELET TRANSFORM IN-DEPTH RECOVERY

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12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： HOR, MK CHEN, JYM CHEN, KS ACAD SINICA INST INFORMAT SCITAIPEI 115TAIWAN

ISBN: (纸本)0819413208

In this paper, a number of spatial/spatial-frequency image representations are reviewed. Wavelets have recently generated much interest, both in applied areas as well as in more theoretical ones. Wavelet transform relative to some basic wavelets provides a flexible time- frequency window which automatically narrows when observing high frequency phenomena and widens when studying low frequency environments. As a result, it is suitable for visual information representation. Applications in computer vision such as image compression and image enhancement are examined. method is presented, in which, a N X N subimage is divided into a lot of N X 7 or N X 9 narrow image regions perpendicular to local fringe direction, and then each region is segmented by a corresponding threshold curve. Because the threshold curves can follow fringe's extremum changes, it can avoid the effect of the inhomogeneous grey level distribution caused by diffraction halo and accurate segmen space, a projection operator is used in the spatial-variant deconvolution. Nevertheless, experimental results show that this approximation mechanism can generate the depth map of different images successfully.

关键词： Wavelets Wavelet transforms Cameras computer vision technology Machine vision Image processing Robot vision robots Deconvolution Space operations

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PROGRESS IN HIGH-LEVEL EXPLORATORY vision 12

PROGRESS IN HIGH-LEVEL EXPLORATORY VISION

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12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： BRAND, M NORTHWESTERN UNIV INST LEARNING SCIEVANSTONIL 60201

ISBN: (纸本)0819413208

We have been exploring the hypothesis that vision is an explanatory process, in which causal and functional reasoning about potential motion plays an intimate role in mediating the activity of low-level visual processes. In particular, we have explored two of the consequences of this view for the construction of purposeful vision systems: Causal and design knowledge can be used to (1) drive focus of attention, and (2) choose between ambiguous image interpretations. An important result of visual understanding is an explanation of the scene's causal structure: How action is originated, constrained, and prevented, and what will happen in the immediate future. In everyday visual experience, most action takes the form of motion, and most causal analysis takes the form of dynamical analysis. This is even true of static scenes, where much of a scene's interest lies in how possible motions are arrested. This paper describes our progress in developing domain theories and visual processes for the understanding of various kinds of structured scenes, including structures built out of children's constructive toys and simple mechanical devices.

关键词： Visualization Visual analytics Buildings robots computer vision technology Machine vision Motion analysis Pathology Robot vision Visual process modeling

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IMAGE-ANALYSIS OF PHOTOCHROMIC INK FOR SECURITY APPLICATIONS 12

IMAGE-ANALYSIS OF PHOTOCHROMIC INK FOR SECURITY APPLICATIONS

引用

12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： BATCHELOR, B STEPHENS, N UNIV WALES COLL CARDIFF COLL CARDIFFDEPT COMP MATHCARDIFF CF1 3NSS GLAMWALES

ISBN: (纸本)0819413208

Photochromic materials exist in two different color states, with switching between states being achieved by irradiation, with ultra-violet and visible light. By printing patterns and data using both photochromic ink and ordinary ink, it is possible to create a document that is difficult to forge and easy to authenticate. Security is achieved only by public ignorance about and the relative rarity of photochromic materials. Very high levels of security are possible, using modern data encipherment techniques. These are so secure that no known algorithmic method exists for breaking them in a practical amount of time. It should be understood that encipherment algorithms provide a way of protecting a message. Guaranteeing the authenticity of a complete document is better achieved using photochromic materials. This article describes a scheme which employs both techniques to achieve higher overall security than either can provide individually. Central to this idea is the ability to sense the presence of photochromic materials using machines, prior to recognizing specified patterns and reading text.

关键词： computer security Photochromic materials Computing systems Printing Ultraviolet radiation Image processing Visible radiation Lamps Switches robots

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EXTRACTION OF EDGE-BASED AND REGION-BASED FEATURES FOR OBJECT RECOGNITION 12

EXTRACTION OF EDGE-BASED AND REGION-BASED FEATURES FOR OBJEC...

引用

12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： COUTTS, B RAVI, S HU, GZ SHRIKHANDE, N CENT MICHIGAN UNIV DEPT COMP SCIMT PLEASANTMI 48858

ISBN: (纸本)0819413208

One of the central problems of computer vision is object recognition. A catalogue of model objects is described as a set of features such as edges and surfaces. The same features are extracted from the scene and matched against the models for object recognition. Edges and surfaces extracted from the scenes are often noisy and imperfect. In this paper algorithms are described for improving low level edge and surface features. Existing edge extraction algorithms are applied to the intensity image to obtain edge features. Initial edges are traced by following directions of the current contour. These are improved by using corresponding depth and intensity information for decision making at branch points. Surface fitting routines are applied to the range image to obtain planar surface patches. An algorithm of region growing is developed that starts with a coarse segmentation and uses quadric surface fitting to iteratively merge adjacent regions into quadric surfaces based on approximate orthogonal distance regression. Surface information obtained is returned to the edge extraction routine to detect and remove fake edges. This process repeats until no more merging or edge improvement can take place. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested using the merging criteria. Results appeared quite encouraging.

关键词： Edge detection Object recognition Image segmentation Algorithm development Feature extraction Detection and tracking algorithms Image processing algorithms and systems computer vision technology Machine vision Visual process modeling

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EXPERT-SYSTEMS AS DESIGN AIDS FOR ARTIFICIAL vision SYSTEMS - A SURVEY 12

EXPERT-SYSTEMS AS DESIGN AIDS FOR ARTIFICIAL VISION SYSTEMS ...

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12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： CREVIER, D UNIV QUEBEC ECOLE TECHNOL SUPERDEPT ELECT ENGNMONTREAL H2T 2C8PQCANADA

ISBN: (纸本)0819413208

The development of software that would be to computer vision what expert system shells are to expert systems has been the subject of considerable inquiry over the last ten years; this paper reviews the pertinent publications and tries to present a coherent view of the field. We start by outlining two major differences between would be `vision shells' and conventional expert system shells. The first is the need for an intermediate level of symbolic representation between image pixels and the knowledge base. The second is that the mental operations that people perform to interpret images lie almost totally below the threshold of consciousness. vision system designers therefore cannot, as domain experts normally do, examine their own mental processes and cast them into rules to extract information from images. The vision shell should thus contain, in addition to the usual knowledge engineering toolbox, knowledge on the pertinence of specific imaging operations towards various goals. After a review of the role of explicit knowledge in artificial vision, we examine the architecture a vision shell should have, and look at ways of facilitating the entry of domain-pertinent knowledge into it. Final remarks are made on knowledge representation and acquisition aspects particular to industrial applications.

关键词： Image segmentation Image processing Machine vision computer vision technology Imaging systems Image analysis Visualization Software development Robot vision robots

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MORPHOLOGICAL SEGMENTATION OF MULTIPROBE FLUORESCENCE IMAGES FOR IMMUNOPHENOTYPING IN MELANOMA TISSUE-SECTIONS 12

MORPHOLOGICAL SEGMENTATION OF MULTIPROBE FLUORESCENCE IMAGES...

引用

12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： DOW, AI SHAFER, SA WAGGONER, AS CARNEGIE MELLON UNIV CTR LIGHT MICROSCOPE IMAGING & BIOTECHNOLPITTSBURGHPA 15213

ISBN: (纸本)0819413208

A fundamental task in studying the action of cancer chemotherapy is to determine the quantity and spatial relationship of tumor-infiltrating lymphocyte populations. Classically this is performed by staining thin tissue sections with antibodies by immunoperoxidase amplification. The staining technique is practically limited to locating a single cell type per tissue section. Full immunophenotyping requires successive staining of serial sections, using statistical analysis to correlate the results. This paper describes a system that brings together multi- parameter fluorescence imaging and morphological segmentation techniques to provide a fast, accurate, and automatic analysis of the lymphocyte infiltrate in tissue sections. With fluorescence techniques a single section can be stained with up to four distinct fluorescently labelled antibodies to determine cell phenotypes. To harness this potential computer vision techniques are required to analyze the images. A routine based on the water shed algorithm has been developed that segments the nuclei image with an accuracy of greater than 90%. By matching the nuclei boundaries to the local peak fluorescence, cell boundary estimates are obtained in the antigen images. By then extracting two measurements from the boundary signal the cells can be classified according to their antigen expression. Determining cell expression of multiple antigens simultaneously provides a more detailed and accurate picture of the tumor infiltrate than single parameter analysis, and increases understanding of the immune response associated with the chemotherapy.

关键词： Image segmentation Tissues Luminescence computer vision technology Machine vision Image filtering Robot vision robots Image analysis Melanoma

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COMPUTING STATISTICAL PROPERTIES OF HUE DISTRIBUTIONS FOR COLOR IMAGE-ANALYSIS 12

COMPUTING STATISTICAL PROPERTIES OF HUE DISTRIBUTIONS FOR CO...

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12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： CREVIER, D UNIV QUEBEC ECOLE TECHNOL SUPERDEPT ELECT ENGNMONTREAL H2T 2C8PQCANADA

ISBN: (纸本)0819413208

Color images can be analyzed using two kinds of coordinate systems: rectangular systems based on primary colors (RGB), and cylindrical systems based on hue, saturation, and intensity (HSI). HSI systems match our intuitive understanding of colors and make it possible to name colors in knowledge bases, a significant advantage given the mushrooming use of declarative knowledge for image analysis. On the other hand, HSI systems give rise to singularities which result in undesirable instabilities, notably with respect to the statistical properties of hue distributions. Computing the mean and variance of a split distribution in the conventional manner would yield an unrealistically large variance and a mean hue in the blue-green region. The paper presents alternative ways of computing means and variances that avoid these effects. At the cost of a relatively slight numerical overhead, these computations generate results in agreement with our intuitive understanding of colors in split peak situations, and reduce to the standard definitions in well-behaved histograms. Recursive formulas are given for the calculation of these statistics, and an efficient algorithm is presented. Equivalence conditions between the results of the introduced procedures and conventional calculations are stated. Examples are given using actual color images.

关键词： computer vision technology Image analysis Machine vision Robot vision robots Statistical analysis Image segmentation Aluminum Nose RGB color model

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SPATIOTEMPORAL TOPOLOGY AND TEMPORAL SEQUENCE IDENTIFICATION WITH AN ADAPTIVE TIME-DELAY NEURAL-NETWORK 12

SPATIOTEMPORAL TOPOLOGY AND TEMPORAL SEQUENCE IDENTIFICATION...

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12th Conference on intelligent robots and computer vision: algorithms and techniques

作者： LIN, DT LIGOMENIDES, PA DAYHOFF, JE UNIV MARYLAND DEPT ELECT ENGNCYBERNET RES LABCOLL PKMD 20742

ISBN: (纸本)0819413208

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

关键词： Neural networks Robot vision robots computer vision technology Image segmentation Machine vision Signal processing Adaptive optics Analytical research Network architectures

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