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Journal ArticleDOI

A survey on industrial vision systems, applications and tools

10 Feb 2003-Image and Vision Computing (Elsevier)-Vol. 21, Iss: 2, pp 171-188
TL;DR: The state of the art in machine vision inspection and a critical overview of real-world applications are presented and two independent ways to classify applications are proposed.
About: This article is published in Image and Vision Computing.The article was published on 2003-02-10. It has received 716 citations till now. The article focuses on the topics: Machine vision.
Citations
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Journal ArticleDOI
TL;DR: It is argued that the next step in the evolution of object recognition algorithms will require radical and bold steps forward in terms of the object representations, as well as the learning and inference algorithms used.

312 citations


Cites background from "A survey on industrial vision syste..."

  • ..., for the automated classification of agricultural products [9]), the electronics and machinery industry (for automated assembly and industrial inspection purposes [10]), and the pharmaceutical industry (for the classification of tablets and capsules) [5]....

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Journal ArticleDOI
TL;DR: Review of various optical inspection approaches in the semiconductor industry and categorize the previous literatures by the inspection algorithm and inspected products to achieve a high robustness and computational efficiency of automated visual inspection.

224 citations

Journal ArticleDOI
TL;DR: This paper intends to survey and evaluate recent advances in data acquisition and progressing, and provide an overview from a manufacturing perspective, some potential manufacturing applications introduced, the technical gaps between the practical requirements and existing technologies discussed, and research opportunities identified.
Abstract: A critical task of vision-based manufacturing applications is to generate a virtual representation of a physical object from a dataset of point clouds. Its success relies on reliable algorithms and tools. Many effective technologies have been developed to solve various problems involved in data acquisition and processing. Some articles are available on evaluating and reviewing these technologies and underlying methodologies. However, for most practitioners who lack a strong background on mathematics and computer science, it is hard to understand theoretical fundamentals of the methodologies. In this paper, we intend to survey and evaluate recent advances in data acquisition and progressing, and provide an overview from a manufacturing perspective. Some potential manufacturing applications have been introduced, the technical gaps between the practical requirements and existing technologies discussed, and research opportunities identified.

176 citations

Journal ArticleDOI
TL;DR: A survey on the latest methods of moving object detection in video sequences captured by a moving camera and presents the main methods which proposed improvements in the general concept of the techniques.

176 citations


Cites background from "A survey on industrial vision syste..."

  • ...Introduction In the field of computer vision, detection of moving objects from a video sequence, which is based on representing moving objects by a binary mask in each frame, is an important issue and interested in many vision based applications such as action recognition [1], traffic controlling [2], industrial inspection [3], human behavior identification [4], and intelligent video surveillance [5]....

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Journal ArticleDOI
TL;DR: A new 3D dynamic imaging technique, Micro Fourier Transform Profilometry (μFTP), which can realize an acquisition rate up to 10,000 3D frame per second (fps), and reconstruct an accurate, unambiguous, and distortion-free 3D point cloud with every two projected patterns.

171 citations

References
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Book
01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Abstract: From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required

52,797 citations

Book
01 Jan 2002

17,039 citations

Journal ArticleDOI
01 May 1993
TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Abstract: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data pairs. In the simulation, the ANFIS architecture is employed to model nonlinear functions, identify nonlinear components on-line in a control system, and predict a chaotic time series, all yielding remarkable results. Comparisons with artificial neural networks and earlier work on fuzzy modeling are listed and discussed. Other extensions of the proposed ANFIS and promising applications to automatic control and signal processing are also suggested. >

15,085 citations

01 Jan 1989

12,457 citations

Journal ArticleDOI
TL;DR: The fuzzy ARTMAP system is compared with Salzberg's NGE systems and with Simpson's FMMC system, and its performance in relation to benchmark backpropagation and generic algorithm systems.
Abstract: A neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors, which may represent fuzzy or crisp sets of features. The architecture, called fuzzy ARTMAP, achieves a synthesis of fuzzy logic and adaptive resonance theory (ART) neural networks by exploiting a close formal similarity between the computations of fuzzy subsethood and ART category choice, resonance, and learning. Four classes of simulation illustrated fuzzy ARTMAP performance in relation to benchmark backpropagation and generic algorithm systems. These simulations include finding points inside versus outside a circle, learning to tell two spirals apart, incremental approximation of a piecewise-continuous function, and a letter recognition database. The fuzzy ARTMAP system is also compared with Salzberg's NGE systems and with Simpson's FMMC system. >

2,096 citations