Organic photoresponsive materials can undergo various reversible variations in certain physical and chemical properties, such as optical properties, electrochemical properties, conformation, and conductivity, upon photoirradiation. They have been widely applied in various optoelectronic fields, especially in information storage. We summarize research progress on organic photoresponsive materials for information storage. First, the design strategies and photoswitching mechanisms for various kinds of organic photoresponsive materials, including small organic molecules, metal complexes, polymers, supramolecules, and cholesteric liquid crystals, are systematically summarized. These materials exhibit reversible changes of absorption and/or emission properties in response to different wavelengths of light. Subsequently, the applications of these organic materials in information storage, such as data (re)writing and erasing, encryption and decryption, and anticounterfeiting, are introduced in detail. Finally, the current challenges and future directions in this rapidly growing research field are discussed. The review will provide important guidance on the future works about the design of excellent organic photoresponsive materials for optoelectronic applications.
In this paper, a novel methodology is presented to settle the region of interest (ROI) detection problem in vehicle color recognition so as to remove the redundant components of vehicles that interfere greatly with color recognition. In order to make full use of the local color and spatial information, vehicle images are divided into different superpixels at first. The spatial relationship between superpixels and the outermost pixels is then used for the background removal of vehicle images. By comparing with the vehicle window clustering centroids obtained by k-means, the superpixels close to the universal color characteristics of windows are removed so that the dominant color superpixels are determined. Finally, a linear Support Vector Machine classifier is trained for color recognition. The experiments demonstrate that the proposed methodology is effective for color region of interest detection and thus contribute to vehicle color recognition.
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