143 research outputs found

    Emerging Applications of Reversible Data Hiding

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    Reversible data hiding (RDH) is one special type of information hiding, by which the host sequence as well as the embedded data can be both restored from the marked sequence without loss. Beside media annotation and integrity authentication, recently some scholars begin to apply RDH in many other fields innovatively. In this paper, we summarize these emerging applications, including steganography, adversarial example, visual transformation, image processing, and give out the general frameworks to make these operations reversible. As far as we are concerned, this is the first paper to summarize the extended applications of RDH.Comment: ICIGP 201

    Traffic sign detection using a cascade method with fast feature extraction and saliency test

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    Automatic traffic sign detection is challenging due to the complexity of scene images, and fast detection is required in real applications such as driver assistance systems. In this paper, we propose a fast traffic sign detection method based on a cascade method with saliency test and neighboring scale awareness. In the cascade method, feature maps of several channels are extracted efficiently using approximation techniques. Sliding windows are pruned hierarchically using coarse-to-fine classifiers and the correlation between neighboring scales. The cascade system has only one free parameter, while the multiple thresholds are selected by a data-driven approach. To further increase speed, we also use a novel saliency test based on mid-level features to pre-prune background windows. Experiments on two public traffic sign data sets show that the proposed method achieves competing performance and runs 27 times as fast as most of the state-of-the-art methods

    Morphological characterization and reconstruction of fractured heat-treated glass

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    Fracture morphology has insightful information related to the residual effect of fractured structural glass, which is vital in assessing the post-fracture performance of glass members. This study experimentally characterized the fracture morphology of heat-treated glass and developed a novel method of morphology reconstruction, which aims to facilitate the numerical analysis of fractured structural glass. With the development of a computer-vision-based method for transparent objects, the morphology information from fragmentation tests was extracted and systematically investigated for monolithic heat-treated glass with various thicknesses, surface compressive stresses and fracture initiation locations, which are considered as the key influencing factors of heat-treated glass fracture. The geometrical features of fragments and their spatial distribution were quantitatively analysed, identifying their correlations with glass properties. The result indicates that the distribution of fragment centroids shows greater dispersion as the tempering level increases, and the fragments tend to be smaller and more rounded. The strain energy release at fracture was also assessed by fracture patterns, showing it presents high sensitivity to the glass thickness and surface compressive stress. Subsequently, a novel approach was proposed for the stochastic reconstruction of fracture morphology, combining feature points distribution and Voronoi tessellation concept. The control parameters are determined by data from the fragmentation tests and the influence of fracture load could be properly considered. The proposed method shows satisfactory outcomes and good agreement with the experimental records, which has further potential in developing refined numerical models by considering more realistic fracture morphology of glass members