Lazar, Anna and Pauwels, Karl and Van Hulle, Marc and Roska, Tamas

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The present work describes a bio-inspired approach designed to solve some tasks raised in the ‘Bionic Eyeglass Project’, which aims to help the everyday life of blind or visually impaired people. The purpose of this approach is to provide a specific kind of information or to determine the region of interest (“ROI”) in a low-resolution and unstable video flow recorded with a mobile phone by the visually impaired person. In the present paper we introduce a new stabilization method and three different tasks are resolved: firstly, locating LED (light-emitting diode) indicators, secondly, locating traffic signs, and thirdly, deciding whether there is any switched-on lamp in a room. The test database has been made out of real-life scenes. We provide detailed evaluation results referring to the execution of those tasks. Our descriptive context refers to the recently modeled mammalian retina channel decomposition. Using it we can avoid - at least partially - the classical difficulty that image processing algorithms nowadays face, namely that the intensity or color values of the same object largely depend on the actual lighting conditions. A further difficulty referring to the lamp-detection is that the solution has to be completely independent of the input’s actual brightness. The method we introduce relies only on a single retina channel and achieves a very high accuracy: the ratio of the correct answers is around 99%. The other two tasks are to carry out an approximately real-time ROI-detection algorithm based solely on image information from an unstable low-resolution video-flow containing complex real-life scenes with unconstrained lighting conditions. The accuracy of the introduced methods is around 80%. We also make use of a stabilization algorithm designed especially for this project. In order to yield the desired information, we process channel-data as well as saliency maps. The presented method can be useful in a variety of other application areas.