Computing visual target distinctness through selective filtering, statistical features, and visual patterns

Fdez-Vidal, X.R.; Toet, A.; Garcia, J.A.; Fdez-Valdivia, J.

Computing visual target distinctness through selective filtering, statistical features, and visual patterns

article

2000

Fdez-Vidal, X.R.

Toet, A.

Garcia, J.A.

Fdez-Valdivia, J.

This paper presents three computational visual distinctness measures, computed from image representational models based on selective filtering, statistical features, and visual patterns, respectively. They are applied to quantify the visual distinctness of targets in complex natural scenes. The measure that applies a simple decision rule to the distances between segregated visual patterns is shown to predict human observer performance in search and detection tasks on complex natural imagery, and to correlate strongly with visual target distinctness estimated by human observers.

Topics

Target acquisition Decision theory Feature extraction Image analysis Mathematical models Optical correlation Image representational models Visual target distinctness Computer vision

TNO Identifier

12376

Repository link

https://resolver.tno.nl/uuid:a49b6e95-6e21-4b5d-a94e-12b2e9c846f4

Source

Optical engineering, 39(1), pp. 267-281.

Pages

267-281

Files

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Computing visual target distinctness through selective filtering, statistical features, and visual patterns

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