By Topic

Applications of Computer Vision, 1996. WACV '96., Proceedings 3rd IEEE Workshop on

Date 2-4 Dec. 1996

Filter Results

Displaying Results 1 - 25 of 46
  • Proceedings Third IEEE Applications Of Workshop On Computer Vision

    Page(s): iii - viii
    Save to Project icon | Request Permissions | PDF file iconPDF (259 KB)  
    Freely Available from IEEE
  • Full text access may be available. Click article title to sign in or learn about subscription options.
  • Author index

    Page(s): 290 - 291
    Save to Project icon | Request Permissions | PDF file iconPDF (101 KB)  
    Freely Available from IEEE
  • A machine vision system for the automated classification and counting of neurons in 3-D brain tissue samples

    Page(s): 224 - 229
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1900 KB)  

    Neuron count in various brain structures is an important factor in many neurobiological studies. We describe a machine vision system which uses color images for the automated classification and counting of neurons in tissue samples. Samples are sliced into registered sections whose thickness is on the order of the diameter of a neuronal nucleus. Sections are stained so that the spectral transmission functions of the neuronal nuclei differ from the surrounding tissue. Each section is imaged using a light microscope. A Bayesian classifier is used for pixel labeling and a geometric analysis routine is employed to segment neuron regions in each section. The 3D tissue sample is reconstructed using registered neuron regions from each section. An object oriented database management system provides an experimental framework for cataloging neuron classes. Experimental results are presented and compared with results obtained by a histologist View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Placing observers to cover a polyhedral terrain in polynomial time

    Page(s): 77 - 82
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (604 KB)  

    The Art Gallery Problem is the problem of determining the number of observers necessary to cover an art gallery room such that every point is seen by at least one observer. This problem is well known and has a linear solution for the 2 dimensional case, but little is known in the 3-D case. In this paper we present a polynomial time solution for the 3-D version of the Art Gallery problem. Because the problem is NP-hard, the solution presented is an approximation, and we present the bounds to our solution. Our solution uses techniques from computational geometry, graph coloring and set coverage. A complexity analysis is presented for each step and an analysis of the overall quality of the solution is given View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A computer vision system to detect 3-D rectangular solids

    Page(s): 27 - 32
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (580 KB)  

    We present a computer vision system to detect 3D rectangular objects. We first describe the method to detect rectangular solids in real video/images in arbitrary orientations, positions, distances from the camera and lighting. The method works by detecting junctions and adjacent edges of rectangular solids. If a rough reference image of the background is available, that can also be used. We have tested our system on several hundreds of real images and video sequences. In particular, we evaluated the system performance by plotting receiver operating characteristic carves (probability of detection versus probability of false alarm). These curves were plotted for results on 500 images and video sequences acquired an a scene with rich background structure; that is, the scene had a large number of background lines and rectangles. In such an environment, we achieved 93% detection at a 13% false alarm rate. Potential applications of this system include detection of packing boxes, trailers of trucks and rectangular buildings. This system could be used for video indexing or for video surveillance in a security monitoring system View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mosaicing of paintings on curved surfaces

    Page(s): 44 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (980 KB)  

    The paper presents an approach for reconstructing images painted on curved surfaces. A set of monocular images is taken from different viewpoints in order to mosaic and represent the entire scene. By using a priori knowledge about the support surface of the picture, we derive the surface localization in the camera coordinate system. An automatic mosaicing method is applied on the patterned images in order to obtain the complete scene. The mosaiced scene is visualized on a new synthetic surface by a mapping procedure View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fast range image segmentation using high-level segmentation primitives

    Page(s): 83 - 88
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (560 KB)  

    In this paper we present a novel algorithm for very fast segmentation of range images into both planar and curved surface patches. In contrast to other known segmentation methods our approach makes use of high-level features (curve segments) as segmentation primitives instead of individual pixels. This way the amount of data can be significantly reduced and a very fast segmentation algorithm is obtained. The proposed algorithm has been tested on a large number of real range images and demonstrated good results. With an optimized implementation our method has the potential to operate in quasi real-time (a few range images per second) View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Passive navigation using focus of expansion

    Page(s): 64 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB)  

    The goal of this work is to propose a method to solve the problem of passive navigation with visual means. The method is a two stage approach: matching of feature extracted from 2D images of a sequence at different times and egomotion parameter computation. Both algorithms are based on a least-square-error technique to minimize appropriate energy functions. Experimental results obtained in real context show the robustness of the method View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Control of scene reconstruction using explicit knowledge

    Page(s): 15 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (964 KB)  

    Applications such as landscape planning, environmental monitoring, and flight and driving simulators have a high demand for realistic landscape models. Quantity, precision and the type of models ask for methods which automate the model generation by evaluation of remote sensing data. The presented modelling system AIDA tackles the demand for efficient representation and high realism by integrating a priori knowledge about the appearance of the objects in the scene to drive object specific constraints for 3D reconstruction. This requires an image interpretation to assign a meaning to the objects in the scene. For explicit representation of the declarative and procedural knowledge a problem independent formalism based on semantic nets and rules is used. It provides both a data driven and model driven control strategy View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Cartographic indexing into a database of remotely sensed images

    Page(s): 8 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (948 KB)  

    The paper aims to develop simple statistical methods for indexing line patterns. The application vehicle used in this study involves indexing into an aerial image database using a cartographic model. The images contained in the database are of urban and semi urban areas. The cartographic model represents a road network known to appear in a subset of the images contained within the database. There are known to be severe imaging distortions present and the data cannot be recovered by applying a simple Euclidean transform to the model. We effect the cartographic indexing into the database using pairwise histograms of the angle differences and the cross ratios of the lengths of line segments extracted from the raw aerial images. We investigate several alternative ways of performing histogram comparison. Our conclusion is that the Matusita and Bhattachargya distances provide significant performance advantages over the L2 norm employed by M. Swain and D. Ballard (1990). Moreover, a sensitivity analysis reveals that the angle difference histogram provides the most discriminating index of line structure; it is robust both to image distortion on to the variable quality of input line segmentation View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mosaic image generation on a flattened Gaussian sphere

    Page(s): 50 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (652 KB)  

    Mosaicing of images is the task of fusing a collection of images with smaller fields of view to obtain an image with a larger field of view. In order to accomplish this task, images should be geometrically and radiometrically corrected. We propose a new approach for perspective correction, useful when smaller images are gathered by rotating a camera with a fixed position. These images are projected onto a Gaussian sphere centered at the focal point of the camera which is later flattened on a plane tangent to the sphere. Using this procedure a field of view of up to 360° can be obtained on a mosaic image. We illustrate the geometric correction capability of our procedure (including more traditional gray level modification and seam elimination techniques) on outdoor scene images that partly overlap with each other View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Video indexing through integration of syntactic and semantic features

    Page(s): 90 - 95
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (744 KB)  

    This paper proposes a content-based video indexing system which provides the functionalities necessary for automatic management of video data through integration of syntactic and semantic features. The proposed system has been applied to detection, classification and then indexing of news programs collected from different TV channels. Although the paper focuses on news programs, the same methods can be used to extent-based index and search other TV programs with distinct semantic structure View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Position estimation from outdoor visual landmarks for teleoperation of lunar rovers

    Page(s): 156 - 161
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (720 KB)  

    The paper presents a new application of computer vision to space robotics: a teleoperation interface which analyzes images sent by a mobile robot in space missions and produces position estimates based an the images. The estimates are displayed to the robot operator as additional information to prevent loss of orientation. The current version of the interface detects mountain formations in images and automatically searches for mountain peaks in a given topographic map. A new algorithm for position estimation uses a statistical description of the various disturbances and signals in the measurement process to produce estimates. The authors have tested the system with real images obtained in the Pittsburgh East and Dromedary Peak USGS quadrangles; they report significant improvements in speed and accuracy compared to previous systems View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive quantization of color space for recognition of finished wooden components

    Page(s): 252 - 257
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (728 KB)  

    The paper concerns the recognition of textured objects, such as stained wooden parts, using color images. Many existing color classification systems utilize histogram-based similarity measures to compare an observed image with models from a database. Although the performance of these systems depends heavily on proper quantization of the color space, most quantization methods are based on traditional clustering or thresholding operations. The authors describe a novel approach to color space quantization in which the intersection of meaningful representations results in a partition of the color space. The color descriptions are chosen adaptively, using a set of training images. The resulting partition serves as the domain for histograms of models and of observed images and information-theoretic similarity measures are used to perform recognition. The motivation for this system is to achieve high recognition accuracy in an industrial setting. Laboratory tests have demonstrated a high level of accuracy for this technique, even though the objects of interest exhibit large variations of texture and color View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • 3L fitting of higher degree implicit polynomials

    Page(s): 148 - 153
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (532 KB)  

    Implicit polynomial 2D curves and 3D surfaces are potentially among the most useful object or data representations for use in computer vision and image analysis. This is because of their interpolation property, Euclidean and affine invariants, and Bayesian recognizers. The paper studies and compares various fitting algorithms in a unified framework of stability analysis. It presents a new robust 3L fitting method that is repeatable, numerically stable and computationally fast and can be used for high degree implicit polynomials to capture complex object structure. With this, the authors lay down a foundation that enables a technology based on implicit polynomial curves and surfaces for applications in indexing into pictorial databases, robot vision, CAD for free-form shapes, etc View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Image processing for computer-aided diagnosis of lung cancer by CT(LSCT)

    Page(s): 236 - 241
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB)  

    This paper reports the image processing technique for computer-aided diagnosis of lung cancer by CT(LSCT). LSCT is the newly developed mobile-type CT scanner for the mass screening of lung cancer by our project team. In this new LSCT system, one essential problem is the increase of image information to about 30 slices per person from 1 X-ray film. To solve this difficult problem, we tried to reduce the image information drastically to be displayed for the doctor, by image processing techniques View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust automatic target recognition in second generation FLIR images

    Page(s): 194 - 201
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (788 KB)  

    In this paper we present a system for the detection and recognition of targets in second generation forward looking infrared (FLIR) images. The system uses new algorithms for target detection and segmentation of the targets. Recognition is based on a methodology far target recognition by parts. A diffusion based approach for determining the parts of a target is also presented here. Experimental results on a large database of FLIR images validate the robustness of the system, and its applicability to FLIR imagery obtained from real scenes View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Automatic measurement of vertebral shape using active shape models

    Page(s): 176 - 180
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (732 KB)  

    The authors describe how active shape models (ASMs) have been used to accurately and robustly locate vertebrae in lateral dual energy X-ray absorptiometry (DXA) images of the spine. DXA images are of low spatial resolution, and contain significant random and structural noise, providing a difficult challenge for object location methods. All vertebrae in the image were searched for simultaneously, improving robustness in location of individual vertebrae by making use of constraints on shape provided by the position of other vertebrae. They show that the use of ASMs with minimal user interaction allows accuracy to be obtained which is as good as that achievable by human operators using a standard manual method View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Analysis of moire patterns in non-uniformly sampled halftones

    Page(s): 208 - 213
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (664 KB)  

    We analyze the moire patterns in halftone images scanned by a popular commercial scanner. We show that the non uniform sampling scheme employed by the scanner introduces extra aliasing components compared to uniform sampling and thus complicates the moire patterns formed. The analysis applies to other scanners that employ non uniform sampling. We also suggest methods for suppressing the moire patterns in scanned halftones View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An evolutive OCR system based on continuous learning

    Page(s): 272 - 277
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (608 KB)  

    The paper presents an evolutive OCR system based on a cooperation between the recognition stage and the contextual stage which makes possible continuous training. The authors use the contextual correction in order to modify the behavior of the recognition stage by adjusting the internal representation of character models. They also introduce a specific classifier suitable for continuous training. The proposed classifier is based on the k-nearest neighbor rule modified by the introduction of weights. During the continuous training, the system selects models of pattern which contribute actively to a correct recognition View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A real-time vision-based 3D motion estimation system for positioning and trajectory following

    Page(s): 264 - 269
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (472 KB)  

    The authors present a real-time vision-based system for automatic positioning and trajectory following, based on a direct method for 3D motion estimation. The spatio-temporal derivatives of the image function, calculated from time-varying imagery, are used to directly calculate the motion and position of the camera. For demonstration, they have implemented the system on a one-degree-of freedom thruster operating in a laboratory water tank. The estimated position information is communicated to the control system, a PID controller, in order to generate the appropriate signal to correct the thruster system's position. The performance of the vision system is demonstrated in selected experiments by comparing results with the data from an optical encoder position sensor View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Choreographed scope manoeuvring in robotically-assisted laparoscopy with active vision guidance

    Page(s): 187 - 192
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (644 KB)  

    This paper presents our research at bringing the state-of-the-art in vision and robotics technologies to enhance the emerging laparoscopic surgical procedure. In particular, a framework utilizing intelligent visual modeling, recognition, and serving capabilities for assisting the surgeon in manoeuvring the scope (camera) in laparoscopy is proposed. The proposed framework integrates top-down model guidance, bottom-up image analysis, and surgeon-in-the-loop monitoring for added patient safety. For the top-down directives, high-level models are used to represent the abdominal anatomy and to encode choreographed scope movement sequences based on the surgeon's knowledge. For the bottom-up analysis, vision algorithms are designed for image analysis, modeling, and matching in a flexible, deformable environment (the abdominal cavity). For reconciling the top-down and bottom-up activities, robot serving mechanisms are realized for executing choreographed scope movements with active vision guidance View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Histogram refinement for content-based image retrieval

    Page(s): 96 - 102
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1572 KB)  

    Color histograms are widely used for content-based image retrieval. Their advantages are efficiency, and insensitivity to small changes in camera viewpoint. However, a histogram is a coarse characterization of an image, and so images with very different appearances can have similar histograms. We describe a technique for comparing images called histogram refinement, which imposes additional constraints on histogram based matching. Histogram refinement splits the pixels in a given bucket into several classes, based upon some local property. Within a given bucket, only pixels in the same class are compared. We describe a split histogram called a color coherence vector (CCV), which partitions each histogram bucket based on spatial coherence. CCVs can be computed at over 5 images per second on a standard workstation. A database with 15,000 images can be queried using CCVs in under 2 seconds. We demonstrate that histogram refinement can be used to distinguish images whose color histograms are indistinguishable View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A real-time vision system for automatic traffic monitoring based on 2D spatio-temporal images

    Page(s): 162 - 167
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (584 KB)  

    The authors present a novel approach using 2D spatio-temporal images for automatic traffic monitoring. A TV camera is mounted above the highway to monitor the traffic through two slice windows for each traffic lane. One slice window is along the lane and the other perpendicular to the lane axis. Two types of 2D spatio-temporal (ST) images are used in the system: the panoramic view image (PVI) and the epipolar plane image (EPI). The real-time vision system for automatic traffic monitoring, VISATRAM, an inexpensive system with a PC 486 and an image frame grabber has been tested with real road images. Not only can the system count the vehicles and estimate their speeds, but it can also classify the passing vehicles using 3D measurements (length, width and height). The VISATRAM works robustly under various light conditions including shadows in the day and vehicle lights at night, and automatically copes with the gradual and abrupt changes of the environment View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.