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Conference on Infrared systems and Photoelectronic Technology

作者： Banish, MR Chenault, DB Harchanko, J Polaris Sensor Technologies Inc. (United States)

ISBN: (纸本)0819455016

A Pulse Coupled Neural Network (PCNN) has been developed in order to segment image data to reduce the amount of downstream processing. This paper discusses the results of applying the PCNN algorithm to data generated by various sensor platforms. The PCNN algorithm was applied to data generated by a Long Wave Infrared Imaging Polarimeter. The PCNN correctly identified the concealed vehicles and the disturbed earth and rejected 96% of the remaining pixels because they had no information content. Next, the results of applying the PCNN algorithm to noisy infrared seeker data are presented. The PCNN correctly identified the target even though the background was quite noisy. Finally, the PCNN algorithm was applied to images containing solar glint. It correctly passed only 3% of the pixels to the downstream target/glint decision algorithm. To obtain maximum data throughput, the PCNN can be implemented in hardware.

关键词： image segmentation Neurons image processing Detection and tracking algorithms image processing algorithms and systems Neural networks Polarimetry Sensors Data processing Infrared imaging

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A knowledge capturing approach for a cooperative intelligent image analysis system

A knowledge capturing approach for a cooperative intelligent...

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Conference on image processing - algorithms and systems III

作者： Ranaweera, KP Samarabandu, J Univ Western Ontario Dept Elect & Comp Engn London ON N6A 5B9 Canada

ISBN: (纸本)0819452017

We present a generalized approach to dynamically incorporate high level knowledge into a cooperative intelligent image analysis framework. We developed this framework in our laboratory to provide a uniform interface to develop intelligent image analysis tools as well as to provide infrastructure facilities required by these tools in order to work cooperatively for accomplishing complex image analysis task goals. This framework is able to automatically generate processing plans which accomplish user defined image analysis task goals. The approach that we propose in this paper provides a flexible interface to incorporate high level knowledge in image processing tools. We provide two ways to develop this knowledge: 1) by taking a feedback from an image processing expert about a processing plan generated by the system;and 2) by accepting a processing plan which accomplishes a particular task from an expert user. and then extracting the high level knowledge encapsulated in this plan. The generalized nature of our approach allows each individual tool to use machine learning algorithms of its own interest in improving the knowledge-base. Preliminary results that we obtained from this work demonstrates the success of our approach.

关键词： image processing image analysis Intelligence systems Human-machine interfaces image segmentation Sensors Digital filtering Gaussian filters image processing algorithms and systems Machine learning

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Automatic partitioning of head CTA for enabling segmentation

Automatic partitioning of head CTA for enabling segmentation

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Medical Imaging 2004 Conference

作者： Suryanarayanan, S Mullick, R Mallya, Y Kamath, V Nagaraj, N GE Co Global Res Imaging Technol Lab Bangalore Karnataka India

ISBN: (纸本)0819452831

Radiologists perform a CT Angiography procedure to examine vascular structures and associated pathologies such as aneurysms. Volume rendering is used to exploit volumetric capabilities of CT that provides complete interactive 3-D visualization. However, bone forms an occluding structure and must be segmented out. The anatomical complexity of the head creates a major challenge in the segmentation of bone and vessel. An analysis of the head volume reveals varying spatial relationships between vessel and bone that can be separated into three sub-volumes: "proximal", "middle", and "distal". The "proximal" and "distal" sub-volumes contain good spatial separation between bone and vessel (carotid referenced here). Bone and vessel appear contiguous in the "middle" partition that remains the most challenging region for segmentation. The partition algorithm is used to automatically identify these partition locations so that different segmentation methods can be developed for each sub-volume. The partition locations are computed using bone, image entropy. and sinus profiles along with a rule-based method. The algorithm is validated on 21 cases (varying volume sizes, resolution, clinical sites, pathologies) using ground truth identified visually. The algorithm is also computationally efficient, processing a 500+ slice volume in 6 seconds (an impressive 0.01 seconds/slice) that makes it an attractive algorithm for pre-processing large volumes. The partition algorithm is integrated into the segmentation workflow. Fast and simple algorithms are implemented for processing the "proximal" and "distal" partitions. Complex methods are restricted to only the "middle" partition. The partition-enabled segmentation has been successfully tested and results are shown from multiple cases.

关键词： Bone Head image segmentation Algorithm development Skull Visualization image processing algorithms and systems 3D image processing Arteries Neck

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Robust real-time audiovisual face detection

Robust real-time audiovisual face detection

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Conference on Multisensor, Multisource Information Fusion

作者： Fang, WM Aarabi, P Univ Toronto Artificial Percept Lab Toronto ON M5S 3G4 Canada

ISBN: (纸本)0819453579

This paper presents a face detection system that synergizes audio localization and visual face detection. This audiovisual face detection system is based on microphone sound localization, and image processing algorithms. The system integrates the application of sound localization by Time Delay of Arrival and the iterative application of Adaptive Background Segmentation, to robustly perform real-time face detection on a stream of webcam images. Experimental results using an array of 24 microphones and a fixed-view webcam, show that the audiovisual face detection system is able to perform face detection of success rate 97.5% at 0.82 seconds of convergence time, and 5.8Hz display frame rate, on a Pentium IV 2.5GHz.

关键词： Facial recognition systems image segmentation Detection and tracking algorithms image processing image processing algorithms and systems System integration Visualization

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Delineation Operating Characteristic (DOC) curve for assessing the accuracy behavior of image segmentation algorithms

Delineation Operating Characteristic (DOC) curve for assessi...

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Medical Imaging 2004 Conference

作者： Udupa, JK Zhuge, Y Univ Penn Med Image Proc Grp Dept Radiol Philadelphia PA 19104 USA

ISBN: (纸本)0819452831

In 2002. at this meeting, we presented a framework for the evaluation of image segmentation methods. That framework suggested the consideration of both recognition and delineation tasks and described three groups of factors under precision, accuracy, and efficiency for evaluating segmentation methods. In this paper, focusing on accuracy, we argue that evaluations conducted on particular manifestations of any segmentation method M (as determined by fixed values of the parameters of M) do not characterize the range of behavior of M. To capture the entire range of behavior of M for a given application domain, we describe a method called Delineation Operating Characteristic (DOC) analysis. The DOC curve summarizes the behavior of M and the tradeoff that is inherent in M between false positive and false negative regions within the regions delineated by M. This, we argue, will allow more complete understanding and more meaningful comparison of the relative accuracy of different methods. This analysis may also allow the selection of more optimal manifestations of M for a given application domain. By way of illustration, we demonstrate with examples how DOC curves can be used for comparing the accuracy of several segmentation methods.

关键词： image segmentation image processing algorithms and systems image processing Fuzzy logic Binary data Cadmium Medical imaging Tissues Algorithm development Brain

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Optical wear assessment system for grinding tools

Optical wear assessment system for grinding tools

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6th International Conference on Quality Control by Artificial Vision

作者： Heger, T Pandit, M Univ Kaiserslautern D-67653 Kaiserslautern Germany

ISBN: (纸本)0819449989

The inspection and monitoring of the wear of grinding tools is essential to ensure the quality of the grinding tool surface and the finished product Most of the current methods for examining a grinding tool surface rely on dismounting the grinding tool. Often, the state of the grinding tool surface is checked indirectly by evaluating the quality of the workpiece. We describe the application of image processing, which offers an effective means for in situ inspection and monitoring. It yields more detailed information about the surface and the kind of wear observed than the common methods. By using multidirectional illumination and image fusion, an image with a high degree of relevant information is generated that is then segmented using the wavelet transform (multiscale analysis) and classified to distinguish grains and cavities on the surface. Results of the application of the algorithms for a high-performance grinding tool with CBN grains embedded in a resin base are presented. (C) 2004 SPIE and IST.

关键词： image segmentation image fusion Inspection Wavelet transforms image processing 3D image processing image processing algorithms and systems Wavelets Radium Surface finishing

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A focus of attention mechanism for gaze control within a framework for intelligent image analysis tools

A focus of attention mechanism for gaze control within a fra...

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Conference on image processing - algorithms and systems III

作者： Rodrigo, R Ranaweera, K Samarabandu, J Univ Western Ontario Dept Elect & Comp Engn London ON N6A 5B9 Canada

ISBN: (纸本)0819452017

Focus of attention is often attributed to biological vision system where the entire field of view is first monitored and then the attention is,focused to the object of interest. We propose using a similar approach for object recognition in a color image sequence. The intention is to locate an object based on a prior motive, concentrate on the detected object so that the imaging device can be guided toward it. We use the abilities of the intelligent image analysis framework developed in our laboratory to generate an algorithm dynamically to detect the particular type of object based on the user's object description. The proposed method uses color clustering along with segmentation. The segmented image with labeled regions is used to calculate the shape descriptor parameters. These and the color information are matched with the input description. Gaze is then controlled by, issuing camera movement commands as appropriate. We present some preliminary results that demonstrate the success of this approach.

关键词： image segmentation image processing image analysis Imaging devices Cameras Algorithm development image processing algorithms and systems Control systems Imaging systems Shape analysis

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Time-Lapse microscopy and image processing for stem cell research modeling cell migration

Time-Lapse microscopy and image processing for stem cell res...

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Medical Imaging 2003 Conference

作者： Gustavsson, T Althoff, K Degerman, J Olsson, T Thoreson, AC Thorlin, T Eriksson, P Chalmers Univ Technol Dept Signals & Syst S-41296 Gothenburg Sweden

ISBN: (纸本)0819448338

This paper presents hardware and software procedures for automated cell tracking and migration modeling. A timelapse microscopy system equipped with a computer controllable motorized stage was developed. The performance of this stage was improved by incorporating software algorithms for stage motion displacement compensation and auto focus. The microscope is suitable for in-vitro stem cell studies and allows for multiple cell culture image sequence acquisition. This enables comparative studies concerning rate of cell splits, average cell motion velocity, cell motion as a function of cell sample density and many more. Several cell segmentation procedures are described as well as a cell tracking algorithm. Statistical methods for describing cell migration patterns are presented. In particular, the Hidden Markov Model (HMM) was investigated. Results indicate that if the cell motion can be described as a non-stationary stochastic process, then the HMM can adequately model aspects of its dynamic behavior.

关键词： Motion models Detection and tracking algorithms image segmentation Data modeling Stem cells image processing algorithms and systems Statistical modeling Time lapse microscopy Statistical analysis Filtering (signal processing)

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Active surface model-based adaptive thresholding algorithm by repulsive external force

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JOURNAL OF ELECTRONIC IMAGING 2003年第2期12卷 299-306页

作者： Liu, F Luo, XP Song, XD Hu, DC Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

Inspired by the idea that threshold surface always intersects the image surface at high gradient points, an active surface-based adaptive thresholding algorithm is proposed to get the binarized result. In this model, the external force is designed to be repulsive from the image surface, thus at the equilibrium state the active surface tends to cover the, supporting points of high gradient with smooth property. as well as be away from the image surface locally, which makes the obtained. threshold surface properly, separate the foreground and background. The description of the algorithm,is. in a simple and reasonable energy functional form, and only two parameters need to be tuned, which gives more convenience to the operation. Analysis and comparison for the, experimental. results reveal that it cannot only give the proper thresholding result but also restrain the occurrence of the ghost phenomenon. (C) 2003 SPIE and IST.

关键词： image segmentation Model-based design 3D modeling 3D image processing Algorithm development Control systems Data modeling image processing algorithms and systems Performance modeling Surgery

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Clustering approach to bone and soft tissue segmentation of digital radiographic images of extremities

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JOURNAL OF ELECTRONIC IMAGING 2003年第1期12卷 40-49页

作者： Pakin, SK Gaborski, RS Barski, LL Foos, DH Parker, KJ Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA Rochester Inst Technol Dept Comp Sci Rochester NY 14653 USA Eastman Kodak Co Hlth Imaging Res Lab Rochester NY 14650 USA

We present an algorithm for segmentation of computed radiography (CR) images of extremities into bone and soft tissue regions. The algorithm is region-based in which the regions are constructed using a region-growing procedure based on two different statistical tests. Following the region-growing process, a tissue classification method is employed. The purpose of the classification is to label each region as either bone or soft tissue. This binary classification goal is achieved by using a voting procedure that consists of the clustering of regions in each neighborhood system into two classes. The voting procedure provides a crucial compromise between the local and the global analysis of the image, which is necessary due to strong exposure variations seen on the imaging plate. Also, the existence of regions whose size is large enough such that exposure variations can be observed through them makes it necessary to use overlapping blocks during the classification. After the tissue classification step, the resulting bone and soft tissue regions are refined by fitting a second-order surface to each tissue, and reevaluating the label of each region according to the distance between the region and surfaces. The performance of the algorithm is tested on a variety of extremity images using manually segmented images as the gold standard. The experiments show that our algorithm provides a bone boundary with an average area overlap of 90% compared to the gold standard. (C) 2003 SPIE and IST.

关键词： Tissues image segmentation Bone Natural surfaces image processing algorithms and systems Chromium Gold image processing Medical imaging Binary data

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