%0 Journal Article
%T Unsupervised color coding for visualizing image classification results
%A Raimondo Schettini
%A Simone Bianco
%J Information Visualization
%@ 1473-8724
%D 2018
%R 10.1177/1473871617700682
%X 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
%K Image segmentation
%K high-contrast colors
%K color-class association
%K optimization
%U https://journals.sagepub.com/doi/full/10.1177/1473871617700682