This paper describes an object matching system which is able to extract objects of interest from outdoor scenes and match them. Our application (in the domain of IVHS) involves measuring the average travel time in a r...
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ISBN:
(纸本)0818658274
This paper describes an object matching system which is able to extract objects of interest from outdoor scenes and match them. Our application (in the domain of IVHS) involves measuring the average travel time in a road network. The extraction of the object of interest is performed by fusing multiple cues including motion, color, edges, and model information. Two objects extracted from images captured by two independent cameras at different times are then matched to evaluate their similarity. Color indexing based on histogram matching is used to avoid matching all possible pairs of objects. To resolve ambiguities, further matching is done by measuring the Hausdorff distance between two sets of edge points. The object matching system was given 2 sets of 40 vehicles. It was able to identify 23 of the 30 correct matches and all the false matches were rejected. Color indexing reduced the number of candidates for a match from 40 to 2. This matching accuracy is adequate to obtain a reliable estimate of the average travel time.
We have developed a new computational model for texture perception which is physiologically plausible and mimics human performance. Our model tries to simulate the visual processing.characteristics by incorporating me...
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We have developed a new computational model for texture perception which is physiologically plausible and mimics human performance. Our model tries to simulate the visual processing.characteristics by incorporating mechanisms tuned to detect luminance, orientation, spatial-frequency and color, which are characteristic features of any textural image. We obtained a very good correlation between human performance and our model simulations with various strategic texture patterns. The highlights of our model are incorporation of chromatic mechanisms to treat color images, in addition to grey-level ones, and the extension of the concept of double-opponency beyond color. The model could be utilized in the area of imageprocessing. machine vision and patternrecognition, and scientific visualization.
The All-Nearest Neighbor problem (ANN, for short) is stated as follows: given a set S of points in the plane, determine for every point in S, a point that lies closest to it. The ANN problem is central to VLSI design,...
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ISBN:
(纸本)0818656026
The All-Nearest Neighbor problem (ANN, for short) is stated as follows: given a set S of points in the plane, determine for every point in S, a point that lies closest to it. The ANN problem is central to VLSI design, computer graphics, patternrecognition, and imageprocessing. among others. In this paper we propose time-optimal algorithms to solve the ANN problem for an arbitrary set of points in the plane and also for the special case in which the points are vertices of a convex polygon. Both our algorithms run on meshes with multiple broadcasting. We first establish an Ω(log n) time lower bound for the task of solving an arbitrary n-point instance of the ANN problem, even if the points are the vertices of a convex polygon. This lower bound holds for both the CREW-PRAM and for the mesh with multiple broadcasting.
Document image understanding encompasses the technology required to make paper documents equivalent to other computer exchange media like floppies, tapes, and CDROMs. The physical reader of the paper document is the s...
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Document image understanding encompasses the technology required to make paper documents equivalent to other computer exchange media like floppies, tapes, and CDROMs. The physical reader of the paper document is the scanner just like the physical reader of the floppy is the floppy drive and the physical reader of the tape cartridge is the tape cartridge drive, and the physical reader of the CDROM is the CDROM drive. In the survey presented, we restrict ourselves to documents such as business letters, forms, and scientific and technical articles such as those found in archival journals and technical conferences. Understanding such documents involves estimating the rotation skew of each document page, determining the geometric page layout, labeling blocks as text or non-text, determining the read order for text blocks, recognizing the text of text blocks through an OCR system, determining the logical page layout, and formatting the data and information of the document in a suitable way for use by a word processing.system or by an information retrieval system.< >
This paper presents a sensing approach where photo-transduction, multi-resolution feature extraction, scale-space integration and edge tracking are performed on a mixed (digital-analog) VLSI architecture in order to g...
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This paper presents a sensing approach where photo-transduction, multi-resolution feature extraction, scale-space integration and edge tracking are performed on a mixed (digital-analog) VLSI architecture in order to generate medium-level scene description. The proposed system is mainly targeted for robot vision applications where feature description is preferred to a set of raw or raster 2D images and edge maps. The Multiport Access photo-Receptor (MAR) is a CMOS sensor and represents the main sensory part of this integrated image acquisition system. VLSI also provides means to integrate analog computing, digital controller and DSP co-processor modules which define a powerful sensory chip set for focal plane imageprocessing. A current version of the MAR sensor which implements 256/spl times/256 pixels includes 16 analog spatial filters which simultaneously compute multiresolution edge maps. This unique 2D hexagonal smart sensor approach which performs up to 8.5/spl times/10/sup 9/ arithmetic Op/sec during the acquisition/filtering phase and 25/spl times/10/sup 9/ Logical Op/sec for scale-space integration allows high resolution image capability. It represents a significant improvement for passive sensory units in a compact assembly for computer vision applications.< >
The image Understanding Environment (IUE) project is a five year program, sponsored by ARPA, to develop a common object-oriented software environment for the development of algorithms and application systems. This pap...
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The image Understanding Environment (IUE) project is a five year program, sponsored by ARPA, to develop a common object-oriented software environment for the development of algorithms and application systems. This paper reviews the design of this system and provides an overview of the distributed implementation effort currently underway at Amerinex AI, Advanced Decision Systems, Carnegie Mellon University, and Colorado State University. The ultimate goal of the project is to provide a software infrastructure of class hierarchies, user interface tools, and IU algorithms that are required to carry out state of the art research in image understanding.< >
A novel depth-from-focus technique is introduced that needs only a single image. It is based on a precise knowledge of the 3-D point spread function and requires objects of uniform brightness and simple shapes. Using ...
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A novel depth-from-focus technique is introduced that needs only a single image. It is based on a precise knowledge of the 3-D point spread function and requires objects of uniform brightness and simple shapes. Using adequate low-level imageprocessing.techniques, the true area of the object and the distance from the focal plane is obtained from parameters such as the apparent (blurred) area of the object and the mean brightness in this area. The technique has been applied to measure the size distribution of bubbles submerged by breaking waves. A depth criterion is used to define a virtual measuring volume that is roughly proportional to the size of the bubbles.< >
image monitoring, the process of locating and identifying significant changes or new activities, is one of the most important imagery exploitation tasks. A site model supported image monitoring system which utilizes i...
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image monitoring, the process of locating and identifying significant changes or new activities, is one of the most important imagery exploitation tasks. A site model supported image monitoring system which utilizes image understanding techniques driven by an underlying site model is presented. In our approach, we first register the image to be monitored to an existing site model, which is constructed using the RADIUS Common Development Environment; the regions of interest are then delineated based on site information, camera acquisition parameters, and goals of the image analyst; object extraction is then done using constraints on size, shape, orientation, and shadow of the target object derived from known information about image resolution, 3-D shape of the object, camera viewing and illuminant directions. The results of object detection are used for monitoring changes.< >
In recent years several nonlinear diffusion schemes have been introduced. We discuss the numerical implementation of a number of current nonlinear evolution schemes, using the notion of well-posed differentiation by G...
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In recent years several nonlinear diffusion schemes have been introduced. We discuss the numerical implementation of a number of current nonlinear evolution schemes, using the notion of well-posed differentiation by Gaussian kernels. The infinitesimal change of an image when increasing scale depends on the local differential invariants evaluated at the scale of the image considered, i.e. on terms of the local jet (the set of all spatial partial derivatives at that point). All these differential terms can be obtained in a well-posed fashion by a convolution of the original image with the family of the Gaussian and its derivatives. The nonlinear partial differential evaluation can thus be numerically approximated by an iterative calculation of the appropriate terms in the local jet. Examples are given for medical images.< >
Vista is a software environment supporting the modular implementation and execution of computer vision algorithms. Because it is extensible, portable, and freely available, Vista is an appropriate medium for the excha...
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Vista is a software environment supporting the modular implementation and execution of computer vision algorithms. Because it is extensible, portable, and freely available, Vista is an appropriate medium for the exchange of standard implementations of algorithms. This paper, an overview of Vista, describes its file format, its data abstraction, its conventions for UNIX filter programs and library routines, and its user interface toolkit. Unlike systems that are designed principally to support imageprocessing. Vista provides for the easy creation and use of arbitrary data types, such as are needed for many areas of computer vision research.< >
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