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

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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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The effect of different thresholding methods in RGB Imaging

The effect of different thresholding methods in RGB Imaging

引用

conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Miettinen, J Ailisto, H VTT Elect FIN-90571 Oulu Finland

ISBN: (纸本)081944300X

Typical surface inspection tasks using RGB vision require the analysis of tens of megabytes of image data per second, with low false alarm and error escape rates. Although automatic inspection systems have become more common on production lines, for example in sawmills, there are substantial needs to improve their performance and accuracy. Detection is one very important part of image flow before defect recognition. Detection is used in order to find suspicious regions of the image, containing possibly defective areas, since defect detection has to cope with very high data rates. It has to be based on relative simple methods. In this paper we describe the effect of different thresholding methods in RGB defect detection. Threshold values were calculated for R, G and B channels, difference channels \R-G\, \R-B\ and \G-B\ and for mean values from R, G and B channels. The analysis was performed for pine-wood. Error escape rate and false alarm rates were used as evaluation criteria. In this paper, R and G channel thresholding methods were the best ones.

关键词： machine vision detection threshold color wood

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New developments in optical grating technology for machine vision and industrial sensors

New developments in optical grating technology for machine v...

引用

conference on intelligent robots and computer vision XVI - algorithms, techniques, Active vision, and Materials Handling

作者： Schaefer, R Schwab, J Lauinger, N CORRSYS GmbH (Germany)

ISBN: (纸本)0819426407

We present a number of applications of optical grating technology for use in machine vision and industrial inspection and measurement applications. The gratings are based on an array of prisms that: are both very easy and very cheap to produce. Currently optical gratings are used in industry in temporal/spatial correlation systems using non-coherent white-light illumination Such systems require either the displacement of the object or the displacement of the grating in order to achieve the time signals required for evaluation. New developments in grating manufacturing techniques and electronic signal processing now enable us to electronically simulate and generate the signals required eliminating the requirement for grating or object motion. We also present a range sensor based on a split pupil methodology upon which we are developing a multiple-channel range sensor. We also highlight some of the work we are presently pursuing in multiple-layer gratings, We are investigating the Talbot and Lau self-imaging effects with hopes of using the results to preprocess images. We have also calculated the effect of multiple Bragg planes recorded into holographic materials, which can be used to produce local image transformations. Also summarized is some of the work based on an inverted retina model of the eye which uses multi-layer gratings placed before the photoreceptors to general trichromatic separation of Light and explain a number of physiological effects of vision.

关键词： optical gratings multi-channel range multi-layer gratings length and velocity measurement

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computer vision inspection of rice seeds quality with discriminant analysis

Computer vision inspection of rice seeds quality with discri...

引用

conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Cheng, F Ying, YB Zhejiang Univ Coll Biosyst Engn & Food Sci Hangzhou 310029 Peoples R China

ISBN: (纸本)081945561X

This study was undertaken to develop computer vision-based rice seeds inspection technology for quality control. Color image classification using a discriminant analysis algorithm identifying germinated rice seed was successfully implemented. The hybrid rice seed cultivars involved were Jinyou402, Shanyou10, Zhongyou207 and Jiayou99. Sixteen morphological features and six color features were extracted from sample images belong to training sets. The color feature of 'Huebmean' shows the strongest classification ability among all the features. Computed as the area of seed region divided by area of the smallest convex polygon that can contain the seed region, the feature of 'Solidity' is prior to the other morphological features in germinated seeds recognition. Combined with the two features of 'Huebmean' and 'Solidity', discriminant analysis was used to classify normal rice seeds and seeds germinated on panicle. Results show that the algorithm achieved an overall average accuracy of 98.4% for both of normal seeds and germinated seeds in all cultivars. The combination of 'Huebmean' and 'Solidity' was proved to be a good indicator for germinated seeds. The simple discriminant algorithm using just two features shows high accuracy and good adaptability.

关键词： computer vision rice seeds germinated discriminant analysis

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Autonomous robot navigation using vision and sensor based algorithm

Autonomous robot navigation using vision and sensor based al...

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conference on intelligent robots and computer vision XXIV - algorithms, techniques, and Active vision

作者： Bhandari, Susmita Mathis, Allison Mohiuddin, Kashif Pietrocola, David Restrepo, Maria Ahlgren, David J. Trinity Coll Dept Engn 300 Summit St Hartford CT 06106 USA

ISBN: (纸本)0819464821

ALVIN-VII is an autonomous vehicle designed to compete in the AUVSI intelligent Ground Vehicle Competition (IGVC). The competition consists of two events, the Autonomous Challenge and Navigation Challenge. Using tri-processor control architecture the information from sonar sensors, cameras, GPS and compass is effectively integrated to map out the path of the robot. In the Autonomous Challenge, the real time data from two Firewire web cameras and an array of four sonar sensors are plotted on a custom-defined polar grid to identify the position of the robot with respect to the obstacles in its path. Depending on the position of the obstacles in the grid, a state number is determined and a command of action is retrieved from the state table. The image processing algorithm comprises a series of steps involving plane extraction, morphological analysis, edge extraction and interpolation, all of which are statistically based allowing optimum operation at varying ambient conditions. In the Navigation Challenge, data from GPS and sonar sensors are integrated on a polar grid with flexible distance thresholds and a state table approach is used to drive the vehicle to the next waypoint while avoiding obstacles. Both algorithms are developed and implemented using National Instruments (NI) hardware and LabVIEW software. The task of collecting and processing information in real time can be time consuming and hence not reactive enough for moving robots. Using three controllers, the image processing is done separately for each camera while a third controller integrates the data received through an Ethernet connection.

关键词： autonomous robot image processing navigation sensors algorithm

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Color space conversion for linear color grading

Color space conversion for linear color grading

引用

conference on intelligent robots and computer vision XIX: algorithms, techniques, and Active vision

作者： Lee, DJ AGRI TECH Inc Woodstock VA 22664 USA

ISBN: (纸本)0819438626

Color grading is an important process for various industries such as food processing, fruit and vegetable grading, etc. Quality and price are often determined by the color of product. For example, darker red color for apples means higher price. In color machine vision applications, image is acquired with a color CCD camera that outputs color information in three channels, red, green, and blue. When grading color, these three primary colors must be processed to determine the color level for separation. A very popular color space conversion technique for color image processing is RGB-to-HSI, where HSI represents hue, saturation and intensity, respectively. However, the conversion result is still three-dimensional information that makes determining color grades very difficult. A new color space conversion technique that can be implemented for high-speed real-time processing for color grading is introduced in this paper. Depending on the application, different color space conversion equations must be used. The result of this technique is a simple one-dimensional array that represents different color levels. This linear array makes linear color grading adjustment possible.

关键词： machine vision color space conversion color sorting color grading

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The expanding venue and persistence of planetary mobile robotic exploration - new technology concepts for Mars and beyond

The expanding venue and persistence of planetary mobile robo...

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conference on intelligent robots and computer vision XXI

作者： Schenker, PS Elfes, A Hall, JL Huntsberger, TL Jones, JA Wilcox, BH Zimmerman, WF CALTECH Jet Prop Lab Pasadena CA 91109 USA

ISBN: (纸本)081945155X

The domain and technology of mobile robotic space exploration are fast moving from brief visits to benign Mars surface regions to more challenging terrain and sustained exploration. Further, the overall venue and concept of space robotic exploration are expanding-"from flatland to 3D'-from the surface;to sub-surface and aerial theatres on disparate large and small planetary bodies, including Mars, Venus, Titan, Europa, and small asteroids. These new space robotic system developments are being facilitated by concurrent, synergistic advances in software and hardware technologies for robotic mobility, particularly as regard on-board system autonomy and novel thermo-mechanical design. We outline these directions of emerging mobile science mission interest and technology enablement, including illustrative work at JPL on terrain-adaptive and multi-robot cooperative rover systems, aerobotic mobility, and subsurface ice explorers.

关键词： space robotics mobile robots intelligent robots robotic sensing aerial robots subsurface exploration

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

COMPUTING STATISTICAL PROPERTIES OF HUE DISTRIBUTIONS FOR CO...

引用

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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Testing a structural light vision software by genetic algorithms: Estimating the worst case behavior of volume measurement

Testing a structural light vision software by genetic algori...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Mantere, T Alander, JT Turku Ctr Comp Sci TUCS FIN-20520 Turku Finland

ISBN: (纸本)081944300X

In this study we use genetic algorithms to generate test surfaces for a proposed structured light 3-D vision system in order to estimate the worst case behavior of error tolerances. The object software evaluates surface profiles for measuring volumes of small objects attached on surfaces that are highly constrained while somewhat arbitrarily shaped. The test system tries to find, by using genetic algorithm search, the shape that results the highest relative error of volume. The parameters of the object system to be optimized include laser angle, image size, object step size, and the number of scan directions. The preliminary results got seem to indicate that a genetic algorithm based approach is a beneficial aid in optical system design.

关键词： genetic algorithms image processing 3-D imaging 3-D metrology machine vision simulation structured light vision

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Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

Image understanding systems based on the unifying representa...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Kuvychko, I

ISBN: (纸本)081944300X

vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the "cortical software". Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently "unexplainable" results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both "what" and "where" visual pathways. Such systems can open new horizons for robotic and computer vision industries.

关键词： image understanding mid-level and high-level vision computational intelligence knowledge & vision engines

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