Profiling user color perception for image retrieving

Abstract : The aim of this work is to build a user profile according to his own perception of colors for image retrieving. Images are being processed relying on a standard or initial set of parameters using the fuzzy set theory and the HLS color space (Hue, Lightness, and Saturation). We developed a dynamic construction of the user profile, which will increase his satisfaction by being more personalized and accommodated to his particular needs. We suggest two methods to define the perception and transform it into a profile; the first method is achieved by querying the user and getting answers, which will guide through the process of implementation of the profile; the second method is achieved by comparing different subjects and ending up by an appropriate aggregation. We also present a method that will recalculate the amount of colors in the image based on another set of parameters, so the colorimetric profile of the image is being modified accordingly. Avoiding the repetition of the process at the pixel level is the main target of this phase, because reprocessing each image is time consuming and turned to be not feasible.
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Imad El-Zakhem, Amine Aït-Younes, Hanna Greige, Herman Akdag. Profiling user color perception for image retrieving. Intelligent Multimedia Databases and Information Retrieval: Advancing Applications and Technologies, IGI Global, pp.1-29, 2011, ⟨10.4018/978-1-61350-126-9.ch001⟩. ⟨hal-01291976⟩



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