Image processing algorithm for the identification of Martian dust devil tracks in MOC and HiRISE images

This paper presents a method for automatic identification of dust devils tracks in MOC NA and HiRISE images of Mars. The method is based on Mathematical Morphology and is able to successfully process those images despite their difference in spatial resolution or size of the scene. A dataset of 200 images from the surface of Mars representative of the diversity of those track features was considered for developing, testing and evaluating our method, confronting the outputs with reference images made manually. Analysis showed a mean accuracy of about 92%. We also give some examples on how to use the results to get information about dust devils, namelly mean width, main direction of movement and coverage per scene. (c) 2012 Elsevier Ltd. All rights reserved.

A layer-by-layer film of chitosan in a taste sensor application

Chitosan is alternated with sulfonated polystyrene (PSS) to build layer-by-layer (LBL) films that are used as sensing units in an electronic tongue. Using impedance spectroscopy as the principle method of detection, an array using chitosan/PSS LBL film and a bare gold electrode as the sensing units was capable of distinguishing the basic tastes - salty, sweet, bitter, and sour - to a concentration below the human threshold. The suitability of chitosan as a sensing material was confirmed by using this sensor to distinguish red wines according to their vintage, vineyard, and brands.