Performance-scalable volumetric data classification for online industrial inspection

Aby Jacob Abraham; Mustapha Sadki; R. M. Lea

doi:10.1117/12.460203

8 March 2002 Performance-scalable volumetric data classification for online industrial inspection

Aby Jacob Abraham, Mustapha Sadki, R. M. Lea

Proceedings Volume 4664, Machine Vision Applications in Industrial Inspection X; (2002) https://doi.org/10.1117/12.460203
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

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Aby Jacob Abraham, Mustapha Sadki, and R. M. Lea "Performance-scalable volumetric data classification for online industrial inspection", Proc. SPIE 4664, Machine Vision Applications in Industrial Inspection X, (8 March 2002); https://doi.org/10.1117/12.460203

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KEYWORDS

Inspection

Visualization

Visual analytics

Computed tomography

Databases

Detection and tracking algorithms

Hough transforms

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