Abstract. In this article, we propose a joint halftoning and data hiding technique for color images. To ensure high quality of the printed image, the color direct binary search (CDBS) iterative halftoning algorithm is used. The proposed approach uses the commonly available cyan, magenta and yellow colorants to hide data in the chrominance channels. Orientation modulation is used for data embedding during the iterative CDBS halftoning stage. The detector is using PCA-learned components to extract the embedded data from the scanned image. Experimental results show that this proposed CDBS-based data hiding method offers both higher data hiding capacity and higher robustness to the print-and-scan channel when compared to the state-of-the-art grayscale counterpart method. The relatively high correct detection rate make this approach suitable for applications which require exact extraction of embedded data in prints.
Many image reproduction devices, such as printers, are limited to only a few numbers of printing inks. Halftoning, which is the process to convert a continuous-tone image into a binary one, is, therefore, an essential part of printing. An iterative halftoning method, called Iterative Halftoning Method Controlling the Dot Placement (IMCDP), which has already been studied by research scholars, generally results in halftones of good quality. In this paper, we propose a structure-based alternative to this algorithm that improves the halftone image quality in terms of sharpness, structural similarity, and tone preservation. By employing appropriate symmetrical and non-symmetrical Gaussian filters inside the proposed halftoning method, it is possible to adaptively change the degree of sharpening in different parts of the continuous-tone image. This is done by identifying a dominant line in the neighborhood of each pixel in the original image, utilizing the Hough Transform, and aligning the dots along the dominant line. The objective and subjective quality assessments verify that the proposed structure-based method not only results in sharper halftones, giving more three-dimensional impression, but also improves the structural similarity and tone preservation. The adaptive nature of the proposed halftoning method makes it an appropriate algorithm to be further developed to a 3D halftoning method, which could be adapted to different parts of a 3D object by exploiting both the structure of the images being mapped and the 3D geometrical structure of the underlying printed surface.
Quality assessment is performed through the use of variety of quality attributes. It is crucial to identify relevant attributes for quality assessment. We focus on 2.5D print quality assessment and its quality attributes. An experiment with observers showed the most frequently used
attributes to judge quality of 2.5D prints with and without reference images. Colour, sharpness, elevation, lightness, and naturalness are the top five the most frequently used attributes for both with and without reference cases. We observed that content, previous experience and knowledge,
and aesthetic appearance may impact quality judgement.
The Huawei/3DLife Grand Challenge Dataset provides multimodal recordings of Salsa dancing, consisting of audiovisual streams along with depth maps and inertial measurements. In this paper, we propose a system for augmented reality-based evaluations of Salsa dancer performances. An essential step for such a system is the automatic temporal synchronisation of the multiple modalities captured from different sensors, for which we propose efficient solutions. Furthermore, we contribute modules for the automatic analysis of dance performances and present an original software application, specifically designed for the evaluation scenario considered, which enables an enhanced dance visualisation experience, through the augmentation of the original media with the results of our automatic analyses.
General TermsAlgorithms
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