Gilles Millon

Binary-image comparison with local-dissimilarity quantification

In this paper, we present a method for binary image comparison. For binary images, intensity information is poor and shape extraction is often difficult. Therefore binary images have to be compared without using feature extraction. Due to the fact that different scene patterns can be present in the images, we propose a modified Hausdorff distance (HD) locally measured in an adaptive way. The resulting set of measures is richer than a single global measure. The local HD measures result in a local-dissimilarity map (LDMap) including the dissimilarity spatial layout. A classification of the images in function of their similarity is carried out on the LDMaps using a support vector machine. The proposed method is tested on a medieval illustration database and compared with other methods to show its efficiency.

A fast binary-image comparison method with local-dissimilarity quantification

Image similarity measure is widely used in image processing. For binary images that are not composed of a single shape, a local comparison is interesting but the features are usually poor (color) or difficult to extract (texture, forms). We present a new binary image comparison method that uses a windowed Hausdorff distance in a pixel-adaptive way. It enables to quantify the local dissimilarities and to give their spatial distribution which greatly improves the dissimilarity information. Combined with a support vector machine classifier, this method is successfully tested on a medieval-impression database

Three-dimensional tools for analysis and conservation of ancient wooden stamps

Abstract This paper deals with the analysis and conservation of ancient wooden stamps from museum or library collections. The aim is to provide historians with tools that ease the process of handling and observation of very fragile and unique objects. By performing a three-dimensional imaging of stamps, data are processed in three different ways: (1) adaptive thresholding on the corresponding range image enables visualization for the first time of an image of the actual print produced by the stamp; (2) interactive enhanced rendering provides a realistic and non-photorealistic interactive visualization; and, finally, (3) rapid prototyping production gives a perfect geometrical facsimile of the stamps, preventing any hazards inherent in the handling of the originals.

A new similarity measure using Hausdorff distance map

Image dissimilarity measure is a hot topic. The measuring process is generally composed of an information mining in each image which results in an image signature and then a signature comparison to make the decision about the image similarity. In the scope of binary images, we propose to replace the information mining by a new straight image comparison which does not require a priori knowledge. The second stage is then replaced by a decision process based on the image comparison. The new comparison process is structured as follows: a morphological multiresolution analysis is applied to the two images. Secondly a distance map is constructed at each scale by the computation of the Hausdorff distance, restricted through a sliding-window. A signature is then extracted from the distance map and is used to make the decision. As an application, the algorithm has been successfully tested on an ancient illustration database.

Range image binarization: applications to wooden stamps analysis

This paper deals with the analysis of ancient wooden stamps. The aim is to extract a binary image from the stamp. This image must be the closer to the image produced by inking and using a printing press with the stamps. A range image based method is proposed to extract a stamped image from the stamps. The range image acquisition from a 3D laser scanner is presented. Pre-filtering for range image enhancement is detailed. The range image binarization method is based on an adaptive thresholding. Few simple processes applied on the range image enable a final binarized image computing. The proposed method provides here a very efficient way to perform virtual stampings with ancient wooden stamps.

Hausdorff distance-based multiresolution maps applied to image similarity measure

Abstract Image comparison is widely used in image processing. For binary images that are not composed of a single shape, a local comparison can be interesting because the features are usually poor (colour) or difficult to extract (texture, forms). Thus a new binary image comparison method that uses a windowed Hausdorff distance is presented. It enables local dissimilarities to be quantified in a simple way. The comparison results in a dissimilarity map. These maps are then used to evaluate the image similarity. The evaluation uses a classification step that is based on a comparison of the dissimilarity map histogram with reference histograms. The comparison is carried out at different scales of a multiresolution analysis, allowing the most discriminating scale in a user-defined notion of dissimilarity to be chosen automatically in the learning step. As an application, a database of digitalized ancient illustrations is successfully processed by the new method.

Low-cost system for ancient stamps range image acquisition

A complete and practical range image sensor development is presented in this paper: from the mathematical modeling to the shape reconstruction. This scanner aims to be integrated in a larger collaborative project. The nal goal is to provide a framework to allow easy comparisons of ancient wooden items by historians. Motivations and expected results are clearly stated in accordance to nancial and easy-to-use constraints. In order to alleviate the calibration process a new calibrating pattern is proposed. The pattern allow both calibration of camera and projector. The method is validated with experimental results. Experimental results are given for the calibration process and the range image acquisition. These results have been performed on both real and synthetic data, which allows us to comment quantitative performances as well as qualitative ones. They are quite encouraging and satisfactory.

A wavelet filter criterion for an a-priori evaluation of wavelet coding and denoising performances

Wavelet transforms are used in number of important signal and image processing tasks including image coding. The choice of the filter bank is very important and is directly linked to the efficiency of the compression. An objective criterion to guide the choice of the wavelet filters is pro- posed. It is composed of two indexes. The first one is a frequency index computed from the aliasing of the filters. The second is a spatial index computed from the spread of the coefficients in spatial domain. The quality of a filter is a trade-off between frequency and spatial quality. From these indexes a filter set can be represented by a point in a plan. The abscissa is given by the frequency index and the ordinate by the spatial index. The criterion is computed for various filters that are represented in the defined plan. This gives a tool for comparing wavelet filters. In a second time the coding performances of the filters are estimated. The denoising performances are also estimated. The results shows that the two proposed indexes allow a good estimation of the coding and denoising performances of the wavelet filters.