Journal ArticleDOI
Model-based recognition in robot vision
Roland T. Chin,Charles R. Dyer +1 more
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TLDR
This paper presents a comparative study and survey of model-based object-recognition algorithms for robot vision, and an evaluation and comparison of existing industrial part- recognition systems and algorithms is given, providing insights for progress toward future robot vision systems.Abstract:
This paper presents a comparative study and survey of model-based object-recognition algorithms for robot vision. The goal of these algorithms is to recognize the identity, position, and orientation of randomly oriented industrial parts. In one form this is commonly referred to as the "bin-picking" problem, in which the parts to be recognized are presented in a jumbled bin. The paper is organized according to 2-D, 2½-D, and 3-D object representations, which are used as the basis for the recognition algorithms. Three central issues common to each category, namely, feature extraction, modeling, and matching, are examined in detail. An evaluation and comparison of existing industrial part-recognition systems and algorithms is given, providing insights for progress toward future robot vision systems.read more
Citations
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Noise Adaptation and Threshold Determination in Image Contour Recognition Method Based on Complex Network
Tang Xiao,Wang Yinhe,Wang Qinruo +2 more
TL;DR: The main idea of the approach is to use complex network methodology to extract a feature vector for shape contour recognition under rotation, noise and shelter and an approximation method for Distance Threshold Determining is presented to help modeling the complex networks.
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Spatial Pattern Detection in Structural Bionformatics
TL;DR: This research presents a new major application of 3D geometric pattern discovery in the rapidly developing field of Bioinformatics, which is dealing with the development of algorithms for Molecular Biology applications.
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Probabilistic Relaxation Labeling: A Short Survey on Object Recognition
TL;DR: The Probabilistic Relaxation Labeling (PRL) is one of the popular probabilistic approaches in matching among model and scene and the most important works based PRL are reported.
Proceedings ArticleDOI
HONN approach for automatic model building and 3D object recognition
Ameer Hussein Morad,Yuan Baozong +1 more
TL;DR: This work presents a method for automatic model building from multiple images of an object to be recognized, where knowledge is the invariant features including the object itself, and is extracted by a higher-ordered neural network (HONN) structure.
Book ChapterDOI
Contour Matching Technique for 3D Object Recognition Using Kalman Filter
M. Hanmandlu,V. Shantaram +1 more
TL;DR: This paper presents a contour matching technique using the Kalman filter for the identification of an object model corresponding to an observed object from a list of object models from range data.
References
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Generalizing the hough transform to detect arbitrary shapes
TL;DR: It is shown how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space, which makes the generalized Houghtransform a kind of universal transform which can beused to find arbitrarily complex shapes.
Book
Robot Vision
TL;DR: Robot Vision as discussed by the authors is a broad overview of the field of computer vision, using a consistent notation based on a detailed understanding of the image formation process, which can provide a useful and current reference for professionals working in the fields of machine vision, image processing, and pattern recognition.
Journal ArticleDOI
Fourier Descriptors for Plane Closed Curves
Charles T. Zahn,Ralph Roskies +1 more
TL;DR: It is established that the Fourier series expansion is optimal and unique with respect to obtaining coefficients insensitive to starting point and the amplitudes are pure form invariants as well as are certain simple functions of phase angles.