Print Email Facebook Twitter Computing visual target distinctness through selective filtering, statistical features, and visual patterns Title Computing visual target distinctness through selective filtering, statistical features, and visual patterns Author Fdez-Vidal, X.R. Toet, A. Garcia, J.A. Fdez-Valdivia, J. Publication year 2000 Abstract 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. Subject VisionTarget acquisitionDecision theoryFeature extractionImage analysisMathematical modelsOptical correlationImage representational modelsVisual target distinctnessComputer vision To reference this document use: http://resolver.tudelft.nl/uuid:a49b6e95-6e21-4b5d-a94e-12b2e9c846f4 DOI https://doi.org/10.1117/1.602360 TNO identifier 12376 Source Optical engineering, 39 (1), 267-281 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.