We present a number of autofocusing methods in lighting microscopy for its use in diatom identifica tion. Among these, the Tenengrad method has been considered one of the best. The basic requirements for a practical autofocusing system are speed, sharpness and robustness to noise. Recently other focus measures based on a modified Laplacian method are said to per form better than Tenengrad. We investigate two sound methods based on a modified Tenengrad and a modi fied Laplacian. Measurements show that they provide a reliable and suitable focus measure that outperform similar methods. We investigate the window size anal ysis dependency and perform an univariate analysis on the focus measures. The focusing techniques are im plemented in an automatic slide scanning system for diatom detection and identification for its use in the ADIAC project. 1

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Abstract:In this paper we propose a set of measures to model the concept of homogeneity in path-based image segmentation. We introduce the idea of path homogeneity as the aggregation of resemblances between consecutive pixels in the path. This resemblance is obtained from a measure of resemblance between neighbour pixels. In order to aggregate these resemblance values we propose the use of certain families of t-norms that verify a set of intuitive properties. We have studied the performance and behaviour of these functions through a set of experiments. Finally, we have applied these proposals to obtain fuzzy segmentations from real images.Keywords: image segmentation; fuzzy segmentation; path-based segmentation; fuzzy connectivity; fuzzy colour homogeneity.Reference to this paper should be made as follows: Chamorro-Martínez, J., Sánchez, D., Prados-Suárez, B. and Galán-Perales, E. He has participated and is currently member of the teams of several projects, and he has published more than 30 papers in international journals and conferences. His current main research interests are in the fields of knowledge discovery and data mining, relational databases, information retrieval, fuzzy sets theory and soft computing.

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In this paper, a new frequency-domain approach to represent motions is proposed. The new scheme is based on a band-pass filtering with a set of logGabor spatio-temporal filters. It is well known that one of the main problems of these approaches is that a filter response varies with the spatial orientation of the underlying signal. To solve this spatial dependency, the proposed model allows to recombine information of motions that has been separated in several filter responses due to its spatial structure. For this purpose, motion patterns are detected as invariance in statistical structure across a range of spatio-temporal frequency bands. This technique is illustrated on real and simulated data sets, including sequences with occlusion and transparencies.

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