Fast Euclidean morphological operators using local distance transformation by propagation

We propose a new method to compute the morphological dilation of a binary image with a circular structuring element of any given size, on a discrete lattice. The algorithm is equivalent to applying a threshold on an exact Euclidean distance map, but computations are restricted to a minimum number of pixels. The complexity of this dilation algorithm is compared to the complexity of the commonly used approximation of circular structuring elements and found to have a similar cost, while providing better results

Toward a content-based watermarking scheme

Image watermarking consists in embedding an unnoticeable and indelible mark inside a digital image. Watermarking technologies aims at solving copyright and integrity problems. Nevertheless classical geometrical transforms generally induce a loss of synchronization that prevent the detection of the mark. We propose in this paper a content-based watermarking scheme that uses a feature point detector to link the mark with the content of the image. In this scheme, feature point detection is followed by a triangular tessellation and the signature is embedded in each triangle of the partition. Our results show that the presented scheme is robust to local geometrical transforms and attacks such as Stirmark.Le tatouage d'images consiste à insérer une signature invisible et indélébile dans une image. Il permet de répondre à des problèmes de droit d'auteur ou d'intégrité. Les transformations géométriques peuvent cependant provoquer une perte de synchronisation et ainsi empêcher la détection de la signature. Nous proposons une méthode de tatouage fondée sur le contenu qui utilise un détecteur de points d'intérêts pour lier la signature au contenu de l'image. La détection de point d'intérêts permet de créer une partition triangulaire et la signature est ensuite insérée dans chacun des triangles. Nos résultats montrent que la méthode présentée est robuste aux déformations géométriques tels que Stirmark

Coarse-to-fine textures retrieval in the JPEG 2000 compressed domain for fast browsing of large image databases

In many applications, the amount and resolution of digi- tal images have significantly increased over the past few years. For this reason, there is a growing interest for techniques allowing to efficiently browse and seek information inside such huge data spaces. JPEG 2000, the latest compression standard from the JPEG committee, has several interesting features to handle very large images. In this paper, these fea- tures are used in a coarse-to-fine approach to retrieve specific information in a JPEG 2000 code-stream while minimizing the computational load required by such processing. Practically, a cascade of classifiers exploits the bit-depth and resolution scalability features intrinsically present in JPEG 2000 to progressively refine the classification process. Comparison with existing techniques is made in a texture-retrieval task and shows the efficiency of such approach