Diatom identification: a double challenge called ADIAC
This paper introduces the project ADIAC (Automatic Diatom Identification and Classification), which started in May 1998 and which is financed by the European MAST (Marine Science and Technology) programme. The main goal is to develop algorithms for an automatic identification of diatoms using image information, both valve shape (contour) and ornamentation. The paper presents the goals of the project as well as first results on shape modeling and contour extraction. Public data are available in order to create student projects beyond the ADIAC partnership.

title: Automatic Identification of Diatoms Using Visual Human-Interpretable Features
abstract: In this paper we present an identification scheme for diatoms using visual human-interpretable features. Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photosynthesis. The automatic identification of diatoms has applications in a number of areas, for example, environmental monitoring and climate research. The overall identification is performed by an ensemble of multiple decision trees following the bagging approach. The use of human-interpretable features in contrast to traditional features, such as Fourier descriptors or moment invariants, makes it possible for a human expert to verify the induced decision trees and opens up the possibility of integrating human expert knowledge into automatically derived decision trees.

title: Automatic Identification of Diatoms Using Decision Forests
abstract: A feature based identification scheme for microscopic images of diatoms is presented in this paper. Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photo synthesis. The proposed automatic identification scheme follows a decision tree based classification approach. In this paper two different ensemble learning methods are evaluated and results are compared with those of single decision trees. As test sets two different diatom image databases are used. For each image in the databases general features like symmetry, geometric properties, moment invariants, and Fourier descriptors as well as diatom specific features like striae density and direction are computed.

title: Identification of Diatoms by Grid Graph Matching
abstract: Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photo synthesis. In this paper a graph matching based identification approach for the retrieval of diatoms from an image database is presented. The retrieval is based on the matching of labeled grid graphs carrying texture information of the underlying diatom. A grid graph is a regular, rectangular arrangement of nodes overlaid on an image. Each node of the graph is labeled with texture features describing a rectangular sub-region of the object. Properties of gray level co-occurrence matrices as well as of Gabor wavelets are used as texture features. The method has been evaluated on a diatom database holding images of 188 different diatoms belonging to 38 classes. For the identification of these diatoms recognition rates of more than 90 percent were obtained.

title: Graph Edit Distance with Node Splitting and Merging, and Its Application to Diatom Idenfication
abstract: A new graph matching scheme based on an extended set of edit operations, which include the splitting and merging of nodes, is proposed in this paper. This scheme is useful in applications where the nodes of the considered graphs represent regions extracted by some segmentation procedure from an image. To demonstrate the feasibility of the proposed method, its application to the automatic identification of diatoms (unicellular algae) is described.

title: Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics
abstract: We present an algorithm functioning as a supervisor module in a multi expert decision making machine. It uses the Bayes theory in order to estimate the biases of individual expert opinions. These are then used to calibrate and conciliate expert opinions to one opinion. We present a framework for simulating decision strategies using expert opinions whose properties are easily modifiable. By using real data coming from a person authentication system using image and speech data we were able to confirm that the proposed supervisor improves the quality of individual expert decisions by reaching success rates of 99.5 %.

title: How well does charge reparametrisation account for solvent screening in molecular mechanics calculations? The example of myosin
abstract: The rate constant of an enzyme-catalysed reaction is one of the major target properties to understand protein function. Atomic-detail computer simulations can in principle be used to estimate rate constants from the energy profile along the reaction coordinate. For such simulations, molecular mechanics is combined with a quantum description of the reaction process. In molecular mechanics calculations, the electrostatic field is represented by the Coulomb potential of partial atomic charges which have been parametrised for small building blocks in vacuum and transferred to the macromolecule. In aqueous solution, however, the electrostatic interactions are affected by the solvent polarization. While this can be described by numerically solving the Poisson-Boltzmann equation, it is computationally expensive. A simple approximation to this is to optimally reproduce the electrostatic potential in solution by reparametrising the partial atomic charges in such a way that a simple Coulomb potential can still be used. Such a procedure would allow to perform fast calculations of reaction processes in proteins while accounting for the solvent screening effect. Here, this method is tested on myosin, a motor protein that is both an enzyme and exists in very different conformations.

title: Fusion of audio and video information for multi modal person authentication
abstract: We present an algorithm functioning as a supervisor module in a multi-expert decision making machine. It uses the Bayes theory in order to estimate the biases of individual expert opinions. The biases are used to calibrate and conciliate expert opinions to a single decision. This supervision technique is applied to the real case of a person authentication technique using two modalities, face and speech. The visual part involves the matching of a coarse grid containing Gabor phase information from face images. The acoustic part is performed by a text-dependent speaker verification system based on Hidden Markov Models. Experimental results show that the proposed fusion method improves the quality of individual expert decisions by reaching success rates of 99.5%.

title: Shape Normalisaiton for Face Recognition
abstract: This paper presents methods for shape normalisation of face images. Localisation and shape normalisation are prerequisites for face recognition algorithms like the eigenface approach. Other established face recognition methods like labeled graph matching can also be accelerated by providing normalised face image databases.

title: Face authentication with Gabor information on deformable graphs
abstract: Elastic graph matching has been proposed as a practical implementation of dynamic link matching, which is a neural network with dynamically evolving links between a reference model and an input image. Each node of the graph contains features that characterize the neighborhood of its location in the image. The elastic graph matching usually consists of two consecutive steps, namely a matching with a rigid grid, followed by a deformation of the grid, which is actually the elastic part. The deformation step is introduced in order to allow for some deformation, rotation, and scaling of the object to be matched. This method is applied here to the authentication of human faces where candidates claim an identity that is to be checked. The matching error as originally suggested is not powerful enough to provide satisfying results in this case. We introduce an automatic weighting of the nodes according to their significance. We also explore the significance of the elastic deformation for an application of face-based person authentication. We compare performance results obtained with and without the second matching step. Results show that the deformation step slightly increases the performance, but has lower influence than the weighting of the nodes. The best results are obtained with the combination of both aspects. The results provided by the proposed method compare favorably with two methods that require a prior geometric face normalization, namely the synergetic and eigenface approaches.