Fathallah Nouboud

Image and Signal Processing

In this study we introduce three daylight colored spectra, i.e. spectra with correlated color temperatures near 6500K, for improved color discrimination. This property has been estimated by the volume of the object color solid in a nearly uniform color space based on the DIN99d color difference formula. Three optimized spectra produce about 11% 13% larger volume than the standard D65 illuminant which simulates natural daylight and improve especially the red-green color discrimination. The optimal spectra are the result of similar optimization processes, but differ in shapes, except the common gap in light power in the region 570 nm 610 nm.

Extraction of signatures from check background based on a filiformity criterion

Extracting a signature from a check with a patterned background is a thorny problem in image segmentation. Methods based on threshold techniques often necessitate meticulous postprocessing in order to correctly capture the handwritten information. In this study, we tackle the problem of extracting handwritten information by means of an intuitive approach that is close to human visual perception, defining a topological criterion specific to handwritten lines which we call filiformity. This approach was inspired by the existence in the human eye of cells whose specialized task is the extraction of lines. First, we define two topological measures of filiformity for binary objects. Next, we extend these measures to include gray-level images. One of these measures, which is particularly interesting, differentiates the contour lines of objects from the handwritten lines we are trying to isolate. The local value provided by this measure is then processed by global thresholding, taking into account information about the whole image. This processing step ends with a simple fast algorithm. Evaluation of the extraction algorithm carried out on 540 checks with 16 different background patterns demonstrates the robustness of the algorithm, particularly when the background depicts a scene.

Handwritten Signature Verification: A Global Approach

This paper presents an off-line handwritten signature verification system based on a global approach. The signature is represented by characteristic curves extracted from its image. These curves describe the general shape of the signature and ignore the slight details that vary from a genuine signature to another. The verification is based on the comparison of characteristic curves by dynamic programming, which is a very powerful method for curves comparison. The experimental results are very promising. Some improvements of the comparison method are under way. A large database is under construction and other methods are being explored (neural networks, geometric parameters,..).

Faber-Schauder Wavelet Transform, Application to Edge Detection and Image Characterization

The Faber-Schauder wavelet transform is a simple multiscale transformation with many interesting properties in image processing. Some of these properties are: preservation of pixel ranges, arithmetic operations, non requirement of boundary processing, multiscale edge detection, elimination of the constant and the linear correlation, and the use of close neighboring information. In this study we describe this transformation and we propose a mixed scale visualization of the wavelet transform which makes it possible to show the transform result as an image. This visualization is used, with orientation information, to refine edge detection and image characterization by selecting regions with a high density of extrema wavelet coefficients.

A Pretopological Approach for Image Segmentation and Edge Detection

We present an approach based on a pretopological formalism that allows the mathematical modeling of image segmentation by region growing. The choice of pretopology is motivated by the fact that it has less axioms than the topology which facilitates its adaptation to discrete spaces and in particularly image processing. In our approach, the pretopological adherency function associated to the pretopological structure is defined by a criterion of homogeneity. We apply our approach to the extraction of handwritten information on check background with images of scene and to edge detection. The aggregation from chosen initial germ ends to a closed part of the image composed by a stroke (a line of handwriting) or a line of contours. The evaluation, undertaken on 60 checks with various background images and different images, gives 92% of good results for the extracted handwriting with a complete elimination of the background and good results for edge detection.

Extraction of items from checks

We propose a method to extract the items of a check by applying three sub processes. First, we eliminate the horizontal lines and some remaining background pixels by a subtraction between a virgin model and a filled specimen of a check, after background elimination on both checks. In the second step, each connected object on the image is described by its minimal surrounding rectangular box. A specific distance is defined for each item. Then the box receives the label of an item if it minimizes its specific distance. In the last step, we propose to reconstruct truncated written lines. The reconstruction is based on a simple geometric hypothesis that a written line does not change its curvature when intersecting with graphic background lines. An evaluation made on 60 different checks shows good results of localization and correct reconstruction when the constant curvature hypothesis is respected.

Enumeration of polyominoes inscribed in a rectangle

We develop a number of formulas and generating functions for the enumeration of general polyominoes inscribed in a rectangle of given size according to their area. These formulae are then used for the enumeration of lattice trees inscribed in a rectangle with minimum area plus one.

A STRUCTURAL APPROACH TO ON-LINE CHARACTER RECOGNITION: SYSTEM DESIGN AND APPLICATIONS

This paper presents a real-time constraint-free handprinted character recognition system based on a structural approach. After the preprocessing operation, a chain code is extracted to represent the character. The classification is based on the use of a processor dedicated to string comparison. The average computation time to recognize a character is about 0.07 seconds. During the learning step, the user can define any set of characters or symbols to be recognized by the system. Thus there are no constraints on the handprinting. The experimental tests show a high degree of accuracy (96%) for writer-dependent applications. Comparisons with other system and methods are discussed. We also present a comparison between the processor used in this system and the Wagner and Fischer algorithm. Finally, we describe some applications of the system.

Image Segmentation and Object Extraction for Automatic Diatoms Classification

The diatoms are unicellular algae of great interest in paleontology, aquatic ecology, and forensic medicine, among others. Currently, there are more than 100 000 known species distributed in aquatic ecosystems. For that reason, there is a big interest in the automatic classification of diatom images, however, the preliminary process applied to isolate the diatom from the background is a complex task. In this paper, we propose a segmentation method and an object-extraction procedure to extract the diatom from the background. First, we binarize the image by searching the optimal threshold in the histogram based on its cumulative distribution function. Then we eliminate, under some spatial criteria, all regions other than those that could be part of the diatom. Afterwards, we construct the convex hull of all remaining components. Finally, from this first polygonal approximation, we construct the diatom contour by successive refinements of the convex hull shape.

Computation of the area in the discrete plane: Green’s theorem revisited

Abstract. The detection of the contour of a binary object is a common problem; however, the area of a region, and its moments, can be a significant parameter. In several metrology applications, the area of planar objects must be measured. The area is obtained by counting the pixels inside the contour or using a discrete version of Green’s formula. Unfortunately, we obtain the area enclosed by the polygonal line passing through the centers of the pixels along the contour. We present a modified version of Green’s theorem in the discrete plane, which allows for the computation of the exact area of a two-dimensional region in the class of polyominoes. Penalties are introduced and associated with each successive pair of Freeman displacements along the contour in an eight-connectivity system. The proposed equation is shown to be true and properties of the equation related to the topology of the regions are presented. The proposed approach is adapted for faster computation than the combinatorial approach proposed in the literature.