A study on the evaluation of structure damages for the visual inspection

Ichitsubo, Makoto; Horiguchi, Itaru; Nagamachi, Mitsuo

doi:10.1109/amt.2005.1505396

Cited by 2 publications

(1 citation statement)

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“…There are many applications for AVI systems such as automobile manufacturing [1], Size Measurement [2], Fabric Inspection [3], defect detection in textured materials [4][5] [6], evaluation of structure damage [7], inspection of printed circuit boards [8], quality inspection of food products [9], Space Platforms Inspections [10] and other large industry demands for quality control of their products. The advantages of AVI Systems are mostly accuracy and speed as well as reducing quality control cost in most single product large manufacturing industries.…”

Section: Introductionmentioning

confidence: 99%

Cost-efficient Automated Visual Inspection system for small manufacturing industries based on SIFT

Bohlool

Taghanaki

2008

2008 23rd International Conference Image and Vision Computing New Zealand

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This paper presents a cost efficient Automated Visual Inspection (AVI) system for small industries' quality control system. The complex hardware and software make current AVI systems too expensive to afford for smallsize manufacturing industries. Proposed approach to AVI systems is based on an ordinary PC with a medium resolution camera without any other extra hardware. The Scale Invariant Feature Transform (SIFT) is used to acquire good accuracy and make it applicable for different situations with different sample sizes, positions, and illuminations. Proposed method can detect three different defect types as well as locating and measuring defect percentage for more specialized utilization. To evaluate the performance of this system different samples with different sizes, shapes, and complexities are used and the results show that proposed system is highly applicable to different applications and is Invariant to noise, illumination changes, rotation, and transformation.

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Section: Introductionmentioning

confidence: 99%

Cost-efficient Automated Visual Inspection system for small manufacturing industries based on SIFT

Bohlool

Taghanaki

2008

2008 23rd International Conference Image and Vision Computing New Zealand

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Classification using a three-dimensional sensor in a structured industrial environment

Mikhailov

Jovančević²,

Mokhtari³

2020

J. Electron. Imag.

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Usage of a three-dimensional (3-D) sensor and point clouds provides various benefits over the usage of a traditional camera for industrial inspection. We focus on the development of a classification solution for industrial inspection purposes using point clouds as an input. The developed approach employs deep learning to classify point clouds, acquired via a 3-D sensor, the final goal being to verify the presence of certain industrial elements in the scene. We possess the computer-aided design model of the whole mechanical assembly and an in-house developed localization module provides initial pose estimation from which 3-D point clouds of the elements are inferred. The accuracy of this approach is proved to be acceptable for industrial usage. Robustness of the classification module in relation to the accuracy of the localization algorithm is also estimated. Fig. 1 (a) Robot-based inspection system with three cameras mounted on an end effector and (b) Ensenso N35 3-D sensor.

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A study on the evaluation of structure damages for the visual inspection

Cited by 2 publications

References 0 publications

Cost-efficient Automated Visual Inspection system for small manufacturing industries based on SIFT

Cost-efficient Automated Visual Inspection system for small manufacturing industries based on SIFT

Classification using a three-dimensional sensor in a structured industrial environment

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