Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Alain Trémeau is active.

Publication


Featured researches published by Alain Trémeau.


Pattern Recognition | 1997

A region growing and merging algorithm to color segmentation

Alain Trémeau; Nathalie Borel

In this paper we present a color segmentation algorithm which combines region growing and region merging processes. This algorithm starts with the region growing process which is based on criteria that take into account color similarity and spatial proximity. The resulting regions are then merged on the basis of a criterion that takes into account only color similarity, in order to generate a non-partitioned segmentation of the image being processed in spatially disconnected but colorimetrically similar regions. Adequate attention is then paid to merge non-representative regions into the other ones to proceed to a segmentation which corresponds to the visual judgement.


IEEE Transactions on Image Processing | 2000

Regions adjacency graph applied to color image segmentation

Alain Trémeau; Philippe Colantoni

The aim of this paper is to present different algorithms, based on a combination of two structures of graph and of two color image processing methods, in order to segment color images. The structures used in this study are the region adjacency graph and the line graph associated.We will see how these structures can enhance segmentation processes such as region growing or watershed transformation. The principal advantage of these structures is that they give more weight to adjacency relationships between regions than usual methods. Let us note nevertheless that this advantage leads in return to adjust more parameters than other methods to best refine the result of the segmentation.We will show that this adjustment is necessarily image dependent and observer dependent.


Cognitive Computation | 2011

A Spatiotemporal Saliency Model for Video Surveillance

Tong Yubing; Faouzi Alaya Cheikh; Fahad Fazal Elahi Guraya; Hubert Konik; Alain Trémeau

A video sequence is more than a sequence of still images. It contains a strong spatial–temporal correlation between the regions of consecutive frames. The most important characteristic of videos is the perceived motion foreground objects across the frames. The motion of foreground objects dramatically changes the importance of the objects in a scene and leads to a different saliency map of the frame representing the scene. This makes the saliency analysis of videos much more complicated than that of still images. In this paper, we investigate saliency in video sequences and propose a novel spatiotemporal saliency model devoted for video surveillance applications. Compared to classical saliency models based on still images, such as Itti’s model, and space–time saliency models, the proposed model is more correlated to visual saliency perception of surveillance videos. Both bottom-up and top-down attention mechanisms are involved in this model. Stationary saliency and motion saliency are, respectively, analyzed. First, a new method for background subtraction and foreground extraction is developed based on content analysis of the scene in the domain of video surveillance. Then, a stationary saliency model is setup based on multiple features computed from the foreground. Every feature is analyzed with a multi-scale Gaussian pyramid, and all the features conspicuity maps are combined using different weights. The stationary model integrates faces as a supplement feature to other low level features such as color, intensity and orientation. Second, a motion saliency map is calculated using the statistics of the motion vectors field. Third, both motion saliency map and stationary saliency map are merged based on center-surround framework defined by an approximated Gaussian function. The video saliency maps computed from our model have been compared to the gaze maps obtained from subjective experiments with SMI eye tracker for surveillance video sequences. The results show strong correlation between the output of the proposed spatiotemporal saliency model and the experimental gaze maps.


Eurasip Journal on Image and Video Processing | 2008

Color in image and video processing: most recent trends and future research directions

Alain Trémeau; Shoji Tominaga; Konstantinos N. Plataniotis

The motivation of this paper is to provide an overview of the most recent trends and of the future research directions in color image and video processing. Rather than covering all aspects of the domain this survey covers issues related to the most active research areas in the last two years. It presents the most recent trends as well as the state-of-the-art, with a broad survey of the relevant literature, in the main active research areas in color imaging. It also focuses on the most promising research areas in color imaging science. This survey gives an overview about the issues, controversies, and problems of color image science. It focuses on human color vision, perception, and interpretation. It focuses also on acquisition systems, consumer imaging applications, and medical imaging applications. Next it gives a brief overview about the solutions, recommendations, most recent trends, and future trends of color image science. It focuses on color space, appearance models, color difference metrics, and color saliency. It focuses also on color features, color-based object tracking, scene illuminant estimation and color constancy, quality assessment and fidelity assessment, color characterization and calibration of a display device. It focuses on quantization, filtering and enhancement, segmentation, coding and compression, watermarking, and lastly on multispectral color image processing. Lastly, it addresses the research areas which still need addressing and which are the next and future perspectives of color in image and video processing.


eurographics | 2014

A Survey of Color Mapping and its Applications

Hasan Sheikh Faridul; Tania Pouli; Christel Chamaret; Jurgen Stauder; Alain Trémeau; Erik Reinhard

Color mapping or color transfer methods aim to recolor a given image or video by deriving a mapping between that image and another image serving as a reference. This class of methods has received considerable attention in recent years, both in academic literature and in industrial applications. Methods for recoloring images have often appeared under the labels of color correction, color transfer or color balancing, to name a few, but their goal is always the same: mapping the colors of one image to another. In this report, we present a comprehensive overview of these methods and offer a classification of current solutions depending not only on their algorithmic formulation but also their range of applications. We discuss the relative merit of each class of techniques through examples and show how color mapping solutions can and have been applied to a diverse range of problems.


Archive | 2009

Computational Color Imaging

Alain Trémeau; Raimondo Schettini; Shoji Tominaga

The present paper discusses the concept of subtractive color mixing widely used in color hardcopy applications and shows that a more realistic concept would be “spectral mixing”: the physical description of the coloration of light by printed surfaces comes from the mixing of light components selectively absorbed by inks or dyes during their patch within the printing materials. Some classical reflectance equations for continuous tone and halftone prints are reviewed and considered as spectral mixing laws. The challenge of extending these models to new inkless printing processes based on laser radiation is also addressed.


conference on security, steganography, and watermarking of multimedia contents | 2005

Simple reversible watermarking schemes

Dinu Coltuc; Alain Trémeau

This paper proposes a low computational reversible watermarking approach. An integer transform is defined for pairs of pixels. The transform is invertible and, besides, for some pairs of pixels, the original values are recovered even if the LSBs of the transformed pixels are overwritten. This allows watermarking embedding into image LSB plane without any other data compression scheme. At detection, original image is exactly recovered. The method is of interest for image authentication and data hiding. Experimental results are provided.


european conference on computer vision | 2006

Feature points tracking: robustness to specular highlights and lighting changes

Michèle Gouiffès; Christophe Collewet; Christine Fernandez-Maloigne; Alain Trémeau

Since the precise modeling of reflection is a difficult task, most feature points trackers assume that objects are lambertian and that no lighting change occurs. To some extent, a few approaches answer these issues by computing an affine photometric model or by achieving a photometric normalization. Through a study based on specular reflection models, we explain explicitly the assumptions on which these techniques are based. Then we propose a tracker that compensates for specular highlights and lighting variations more efficiently when small windows of interest are considered. Experimental results on image sequences prove the robustness and the accuracy of this technique in comparison with the existing trackers. Moreover, the computation time of the tracking is not significantly increased.


Computer Graphics Forum | 2016

Colour Mapping: A Review of Recent Methods, Extensions and Applications

H. Sheikh Faridul; Tania Pouli; Christel Chamaret; Jurgen Stauder; Erik Reinhard; D. Kuzovkin; Alain Trémeau

The objective of colour mapping or colour transfer methods is to recolour a given image or video by deriving a mapping between that image and another image serving as a reference. These methods have received considerable attention in recent years, both in academic literature and industrial applications. Methods for recolouring images have often appeared under the labels of colour correction, colour transfer or colour balancing, to name a few, but their goal is always the same: mapping the colours of one image to another. In this paper, we present a comprehensive overview of these methods and offer a classification of current solutions depending not only on their algorithmic formulation but also their range of applications. We also provide a new dataset and a novel evaluation technique called ‘evaluation by colour mapping roundtrip’. We discuss the relative merit of each class of techniques through examples and show how colour mapping solutions can have been applied to a diverse range of problems.


digital image computing: techniques and applications | 2010

A Novel Algorithm for Text Detection and Localization in Natural Scene Images

Sezer Karaoglu; Basura Fernando; Alain Trémeau

Text data in an image present useful information for annotation, indexing and structuring of images. The gathered information from images can be applied for devices for impaired people, navigation, tourist assistance or georeferencing business. In this paper we propose a novel algorithm for text detection and localization from outdoor/indoor images which is robust against different font size, style, uneven illumination, shadows, highlights, over exposed regions, low contrasted images, specular reflections and many distortions which makes text localization task harder. A binarization algorithm based on difference of gamma correction and morphological reconstruction is realized to extract the connected components of an image. These connected components are classified as text and non test using a Random Forest classifier. After that text regions are localized by a novel merging algorithm for further processing.

Collaboration


Dive into the Alain Trémeau's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Raimondo Schettini

University of Milano-Bicocca

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Eric Dinet

Jean Monnet University

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Gaël Chareyron

École Normale Supérieure

View shared research outputs
Researchain Logo
Decentralizing Knowledge