computervision experiments are not very often linked to practical applications but rather deal with typical laboratory experiments under controlled conditions. For instance, most object recognition experiments are ba...
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ISBN:
(纸本)0819419524
computervision experiments are not very often linked to practical applications but rather deal with typical laboratory experiments under controlled conditions. For instance, most object recognition experiments are based on specific models used under limitative constraints. Our work proposes a general framework for rapidly locating significant 3D objects in 2D static images of medium to high complexity, as a prerequisite step to recognition and interpretation when no a priori knowledge of the contents of the scene is assumed. In this paper, a definition of generic objects is proposed, covering the structures that are implied in the image. Under this framework, it must be possible to locate generic objects and assign a significance figure to each one from any image fed to the system. The most significant structure in a given image becomes the focus of interest of the system determining subsequent tasks (like subsequent robot moves, image acquisitions and processing). A survey of existing strategies for locating 3D objects in 2D images is first presented and our approach is defined relative to these strategies. Perceptual grouping paradigms leading to the structural organization of the components of an image are at the core of our approach.
The paper presents a system for the recognition and pose estimation of 3D objects with an emphasis on the segmentation and verification modules. The system is tailored to the analysis of 3D contour images, which are o...
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ISBN:
(纸本)0819419524
The paper presents a system for the recognition and pose estimation of 3D objects with an emphasis on the segmentation and verification modules. The system is tailored to the analysis of 3D contour images, which are obtained from image sequences of a CCD camera by means of Kalman filtering. In order to reduce the search complexity and the noise sensitivity of the recognition process, the method is built on robust contour-based 2D algorithms for the retrieval of model candidates from the database and the generation of pose hypotheses. These techniques apply because of the previous segmentation of the 3D contour image into plane curve segments that make up boundary lines of plane surface patches. Hypotheses for the object's pose are obtained by pairwise matching of model and image boundaries. The subsequent verification computes the best globally consistent assignment of model and image contours by searching for groups of similar pose hypothesis. Both the segmentation and the verification algorithm are formulated in terms of clustering approaches and realized by use of a common technique for the evaluation of transformation space. With regard to industrial applications most importance has been attached to the modular design of a robust software solution and the experimental performance evaluation. Experimental results obtained from real-world images are presented.
Morphological pyramid has been proven to be a useful tool in image compression due to low computational complexity, simple implementation and good compression performance based on minimization of entropy. Several morp...
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ISBN:
(纸本)0819419524
Morphological pyramid has been proven to be a useful tool in image compression due to low computational complexity, simple implementation and good compression performance based on minimization of entropy. Several morphology based pyramid decomposition techniques already exist. These techniques use morphological filters prior to the down sampling of images. The coding schemes developed commonly omit the first error image of the error pyramid to achieve high compression ratios. However, fine image details may be lost in this process. In order to get high quality lossy image, an estimator involving connectivity preserving filters for the first error image has been used. By using this estimator, the bits per pixel required to code the first error image can be reduced by 30 to 40 percent to obtain `near lossless' compression. In this paper, we apply variable Vector Quantization (VQ) to pyramid coding. We compare the performance of the above estimator to that of VQ scheme. For multi- level pyramid, we discuss accumulative errors and use a modified pyramid generation structure to reduce the accumulative errors. We perform our comparison on two standard images and use Peak Signal to Noise Ratio to judge the compression efficiency and visual quality.
In using machine vision for assessing an object's surface quality, many images are required to be processed in order to separate the good areas from the defective ones. Examples can be found in the leather hide gr...
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ISBN:
(纸本)0819419524
In using machine vision for assessing an object's surface quality, many images are required to be processed in order to separate the good areas from the defective ones. Examples can be found in the leather hide grading process; in the inspection of garments/canvas on the production line; in the nesting of irregular shapes into a given surface... . The most common method of subtracting the total area from the sum of defective areas does not give an acceptable indication of how much of the `good' area can be used, particularly if the findings are to be used for the nesting of irregular shapes. This paper presents an image scanning technique which enables the estimation of useable areas within an inspected surface in terms of the user's definition, not the supplier's claims. That is, how much useable area the user can use, not the total good area as the supplier estimated. An important application of the developed technique is in the leather industry where the tanner (the supplier) and the footwear manufacturer (the user) are constantly locked in argument due to disputed quality standards of finished leather hide, which disrupts production schedules and wasted costs in re-grading, re- sorting... . The developed basic algorithm for area scanning of a digital image will be presented. The implementation of an improved scanning algorithm will be discussed in detail. The improved features include Boolean OR operations and many other innovative functions which aim at optimizing the scanning process in terms of computing time and the accurate estimation of useable areas.
Nesting of shoe parts onto a leather hide is a very complex puzzle. This is because firstly, both the shoe parts and the leather hide are of irregular shapes and secondly, leather quality is not uniform throughout the...
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ISBN:
(纸本)0819419524
Nesting of shoe parts onto a leather hide is a very complex puzzle. This is because firstly, both the shoe parts and the leather hide are of irregular shapes and secondly, leather quality is not uniform throughout the hide, certain zones are only suitable for certain types of shoe parts. Moreover, leather hide bears stretch directions which some shoe parts are not permitted to be nested in at certain angles to the hide's stretch directions. Thirdly, the pose of defects in some shoe parts can be acceptable or unacceptable depending on the manufacturer's quality standard. Machine vision researchers have been attempting to capture the hide defect map and use this data file for assisting the computerization nesting of the irregular shapes. There are many challenging tasks in the visual inspection stage which affect the performance of the nesting systems. An essential assignment is the clustering of leather defects. Two vital parameters required in the clustering of defects are the minimum Euclidean distance between defects to be clustered and the re-classification of the newly formed cluster if it contains more than one type of defect or satisfied more serious defect type definition. In order to minimize the wastage in yield, this work recommends that during the inspection stage, only defects of the same type are to be clustered and the process should cease at the point where the newly formed cluster is to become a more serious defect type. The question of minimum Euclidean distance should be considered at both inspection stage as a preliminary clustering operation and at the nesting stage when the shoe size and part shapes are known, as a fine tuned process.
We consider detection (locating all objects in a scene) independent of object distortions and contrast differences and in the presence of clutter. We employ several different new detection algorithms;to reduce false a...
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ISBN:
(纸本)0819419524
We consider detection (locating all objects in a scene) independent of object distortions and contrast differences and in the presence of clutter. We employ several different new detection algorithms;to reduce false alarms. We fuse (combine) the outputs from different detection algorithms. We describe a new peak sorting detection scoring algorithm and 3 different fusion algorithms to combine the results from different algorithms: binary, analog, and hierarchical fusion. Quantitative data on a distortion-invariant six object class is presented;the objects have a wide range of object contrasts including obscured objects and the objects are present in severe clutter.
In computervision, there are many methods to obtain 3D information of objects from images. But the forms of 3D information are different from different methods. For example, in the way of shape from shading, orientat...
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ISBN:
(纸本)0819419524
In computervision, there are many methods to obtain 3D information of objects from images. But the forms of 3D information are different from different methods. For example, in the way of shape from shading, orientation of surface normal can be obtained;in the way of stereo vision, 3D coordinate of points on the object can be obtained. This paper proposes a new method to calculate cross-section area of the object from surface normal by fitting curve. The new method is more precise than old method.
For truly intelligent behavior of a mobile robot, the important ask is to make the mobile robot to understand its environment. For this reason a certain measurement device must be installed in the mobile robot. In our...
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ISBN:
(纸本)0819419524
For truly intelligent behavior of a mobile robot, the important ask is to make the mobile robot to understand its environment. For this reason a certain measurement device must be installed in the mobile robot. In our system we make use of a tri-aural sensor array to observe the robot environment. The tri-aural sensor array is composed of three ultrasonic sensors placed on a line. The central sensor is used as transmitter as well as receiver, the two peripheral ones are used only as receivers. By using this device, the robot can get some environment information which is represented by the reflected echoes from the objects in the sensor field. From the sampled information, the robot has to determine the number of objects as well as their positions (distance and bearing) in the sensor field. How to process these sensor array signals is our principal problem. We have developed two neural network techniques for solving this problem, one is based on a competition neural network and another based on a multi-layer feedforward neural network. In this paper, we first describe the correspondence problem in realistic circumstances and then we briefly introduce both neural network techniques. Finally we compare both methods by using simulation data.
A mobile robot has been designed which incorporates line following, obstacle avoidance and speed control. The line following algorithm images two windows and locates the centroid of the brightest target in the window....
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ISBN:
(纸本)0819419524
A mobile robot has been designed which incorporates line following, obstacle avoidance and speed control. The line following algorithm images two windows and locates the centroid of the brightest target in the window. From these two centroids and the knowledge that the points are in the ground plane, the equation of the line is developed. The angle of the line and minimum distance from the robot centroid are then calculated and used in the steering control. This robot was designed for the 1995 Automated Unmanned Vehicle Society/Society of Automotive Engineers contest and won first place in the design competition.
This causes distortion or no-signal condition and, as a result, deterioration of the accuracy while determining the reference point coordinates. The device performance by isolated CCD defects as well as by no-signal s...
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ISBN:
(纸本)0819419524
This causes distortion or no-signal condition and, as a result, deterioration of the accuracy while determining the reference point coordinates. The device performance by isolated CCD defects as well as by no-signal states in the frame under detection has been investigated. The device has been connected in two-processor circuit: the video-signal processor and the tracking processor implemented in the liner Kalman Filter. The numeric results have been obtained by full-scale modeling of the PC device, by the data accession speed 25 Hz, CCD dimensions 256 × 256 pixels and the track including the deterministic and random components.
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