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Color contributes to object-contour perception in natural scenes

Hansen, Thorsten ; Gegenfurtner, Karl R.


Originalveröffentlichung: (2017) Journal of Vision 17(3):14 doi: 10.1167/17.3.14
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URN: urn:nbn:de:hebis:26-opus-128630
URL: http://geb.uni-giessen.de/geb/volltexte/2017/12863/

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Freie Schlagwörter (Englisch): color , luminance , object-contour perception , natural scenes
Sammlung: Open Access - Publikationsfonds
Universität Justus-Liebig-Universität Gießen
Institut: Psychologie und Sportwissenschaft
Fachgebiet: Psychologie
DDC-Sachgruppe: Psychologie
Dokumentart: Aufsatz
Sprache: Englisch
Erstellungsjahr: 2017
Publikationsdatum: 26.05.2017
Kurzfassung auf Englisch: The magnitudes of chromatic and achromatic edge contrast are statistically independent and thus provide independent information, which can be used for object-contour perception. However, it is unclear if and how much object-contour perception benefits from chromatic edge contrast. To address this question, we investigated how well human-marked object contours can be predicted from achromatic and chromatic edge contrast. We used four data sets of human-marked object contours with a total of 824 images. We converted the images to the Derrington–Krauskopf–Lennie color space to separate chromatic from achromatic information in a physiologically meaningful way. Edges were detected in the three dimensions of the color space (one achromatic and two chromatic) and compared to human-marked object contours using receiver operating-characteristic (ROC) analysis for a threshold-independent evaluation. Performance was quantified by the difference of the area under the ROC curves (?AUC). Results were consistent across different data sets and edge-detection methods. If chromatic edges were used in addition to achromatic edges, predictions were better for 83% of the images, with a prediction advantage of 3.5% ?AUC, averaged across all data sets and edge detectors. For some images the prediction advantage was considerably higher, up to 52% ?AUC. Interestingly, if achromatic edges were used in addition to chromatic edges, the average prediction advantage was smaller (2.4% ?AUC). We interpret our results such that chromatic information is important for object-contour perception.
Lizenz: Lizenz-Logo  Creative Commons - Namensnennung, Nicht kommerziell, keine Bearbeitung 4.0