In this article, we describe a general purpose system that, given as input a segmented/classified image, automatically provides different visual outputs exploiting solid colors, color boundaries, and transparent colors. Moreover, if the names of the classes are given, the system automatically places a textual label in the less salient sub-region of the corresponding class. For color-class association and class label placement, we take into account the underlying image color and structure exploiting both saliency and superpixel representation. The color selection and the color-class association are formulated both as optimization problems and heuristically solved using a Local Search procedure. Results show the effectiveness of the proposed system on images having different content and different number of annotated regions
Bianco, S., & Schettini, R. (2018). Unsupervised color coding for visualizing image classification results. INFORMATION VISUALIZATION, 17(2), 161-177.
Citazione: | Bianco, S., & Schettini, R. (2018). Unsupervised color coding for visualizing image classification results. INFORMATION VISUALIZATION, 17(2), 161-177. |
Tipo: | Articolo in rivista - Articolo scientifico |
Carattere della pubblicazione: | Scientifica |
Presenza di un coautore afferente ad Istituzioni straniere: | No |
Titolo: | Unsupervised color coding for visualizing image classification results |
Autori: | Bianco, S; Schettini, R |
Autori: | |
Data di pubblicazione: | 2018 |
Lingua: | English |
Rivista: | INFORMATION VISUALIZATION |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1177/1473871617700682 |
Appare nelle tipologie: | 01 - Articolo su rivista |