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

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

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

2000

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 (1) to predict human observer performance in search and detection tasks on complex natural imagery, and (2) to correlate strongly with visual target distinctness estimated by human observers.

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

http://resolver.tudelft.nl/uuid:a49b6e95-6e21-4b5d-a94e-12b2e9c846f4

https://doi.org/10.1117/1.602360

12376

Optical engineering, 39 (1), 267-281

article