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Créteil, France

Pedersen M.,Gjovik University College | Bonnier N.,Oce Print Logic Technologies | Hardeberg J.Y.,Gjovik University College | Albregtsen F.,University of Oslo
Journal of Electronic Imaging

The evaluation of perceived image quality in color prints is a complex task due to its subjectivity and dimensionality. The perceived quality of an image is influenced by a number of different quality attributes. It is difficult and complicated to evaluate the influence of all attributes on overall image quality, and their influence on other attributes. Because of this difficulty, the most important attributes of a color image should be identified to achieve a more efficient and manageable evaluation of the image's quality. Based on a survey of the existing literature and a psychophysical experiment, we identify and categorize existing image quality attributes to propose a refined selection of meaningful ones for the evaluation of color prints. © 2010 SPIE and IS&T. Source

Lindner A.,Ecole Polytechnique Federale de Lausanne | Shaji A.,Ecole Polytechnique Federale de Lausanne | Bonnier N.,Oce Print Logic Technologies | Susstrunk S.,Ecole Polytechnique Federale de Lausanne
MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia

With the advent of social image-sharing communities, millions of images with associated semantic tags are now available online for free and allow us to exploit this abundant data in new ways. We present a fast non-parametric statistical framework designed to analyze a large data corpus of images and semantic tag pairs and find correspondences between image characteristics and semantic concepts. We learn the relevance of different image characteristics for thousands of keywords from one million annotated images. We demonstrate the framework's effectiveness with three different examples of semantic image enhancement: we adapt the gray-level tone-mapping, emphasize semantically relevant colors, and perform a defocus magnification for an image based on its semantic context. The performance of our algorithms is validated with psychophysical experiments. © 2012 ACM. Source

Lindner A.,Ecole Polytechnique Federale de Lausanne | Bonnier N.,Oce Print Logic Technologies | Susstrunk S.,Ecole Polytechnique Federale de Lausanne
Proceedings of SPIE - The International Society for Optical Engineering

We present a novel framework for automatically determining whether or not to apply black point compensation (BPC) in image reproduction. Visually salient objects have a larger influence on determining image quality than the number of dark pixels in an image, and thus should drive the use of BPC. We propose a simple and efficient algorithmic implementation to determine when to apply BPC based on low-level saliency estimation. We evaluate our algorithm with a psychophysical experiment on an image data set printed with or without BPC on a Canon printer. We find that our algorithm is correctly able to predict the observers' preferences in all cases when the saliency maps are unambiguous and accurate. © 2010 Copyright SPIE - The International Society for Optical Engineering. Source

Ortiz Segovia M.V.,Purdue University | Bonnier N.,Oce Print Logic Technologies | Allebach J.P.,Purdue University
Proceedings of SPIE - The International Society for Optical Engineering

Ink-saving strategies for CMYK printers have evolved from their earlier stages where the 'draft' print mode was the main option available to control ink usage. The savings were achieved by printing alternate dots in an image at the expense of reducing print quality considerably. Nowadays, customers are not only unwilling to compromise quality but have higher expectations regarding both visual print quality and ink reduction solutions. Therefore, the need for more intricate ink-saving solutions with lower impact on print quality is evident. Printing-related factors such as the way the printer places the dots on the paper and the ink-substrate interaction play important and complex roles in the characterization and modeling of the printing process that make the ink reduction topic a challenging problem. In our study, we are interested in benchmarking ink-saving algorithms to find the connections between different ink reduction levels of a given ink-saving method and a set of print quality attributes. This study is mostly related to CMYK printers that use dispersed dot halftoning algorithms. The results of our efforts to develop such an evaluation scheme are presented in this paper. © 2012 SPIE-IS&T. Source

Felhi M.,CNRS Lorraine Research Laboratory in Informatics and its Applications | Bonnier N.,Oce Print Logic Technologies | Tabbone S.,CNRS Lorraine Research Laboratory in Informatics and its Applications
Proceedings - International Conference on Image Processing, ICIP

In this paper we study the detection of skewed text lines in scanned document images. The aim of our work is to develop a new automatic approach able to estimate precisely the skew angle of text in document images. Our new method is based on Maximum Gradient Difference (MGD) and R-signature. It detects zones that have high variations of gray values in different directions using the MGD transform. We consider these zones as being text regions. R-signature which is a shape descriptor based on Radon transform is then applied in order to approximate the skew angle. The accuracy of the proposed algorithm is evaluated on an open dataset by comparing error rates. © 2011 IEEE. Source

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