Jose Luis Pech-Pacheco

Diatom autofocusing in brightfield microscopy: a comparative study

We present a number of autofocusing methods in light microscopy for use in diatom identification. 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 perform better than Tenengrad. We investigate two sound methods based on a modified Tenengrad and a modified Laplacian. Measurements show that they provide a reliable and suitable focus measure that outperform similar methods. We investigate the window size analysis dependency and perform an univariate analysis on the focus measures. The focusing techniques are implemented in an automatic slide scanning system for diatom detection and identification for its use in the ADIAC project.

Invariant recognition of polychromatic images of Vibrio cholerae O1

Cholera is an acute intestinal infectious disease. It has claimed many lives throughout history, and it continues to be a global health threat. Cholera is considered one of the most important emer- gence diseases due its relation with global climate changes. Automated methods such as optical systems represent a new trend to make more accurate measurements of the presence and quantity of this microorgan- ism in its natural environment. Automatic systems eliminate observer bias and reduce the analysis time. We evaluate the utility of coherent optical systems with invariant correlation for the recognition of Vibrio cholerae O1. Images of scenes are recorded with a CCD camera and decomposed in three RGB channels. A numeric simulation is developed to identify the bacteria in the different samples through an invariant cor- relation technique. There is no variation when we repeat the correlation and the variation between images correlation is minimum. The position-, scale-, and rotation-invariant recognition is made with a scale transform through the Mellin transform. The algorithm to recognize Vibrio cholerae O1 is the presence of correlation peaks in the green channel output and their absence in red and blue channels. The discrimination criterion is the presence of correlation peaks in red, green, and blue channels.

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.

Invariant optical color correlation for recognition of vibrio cholerae 01

The paper evaluates the utility of coherent optical systems with invariant color correlation for the recognition of vibrio cholerae 01 in culturable and nonculturable stage stained with direct immunofluorescence in laboratory and environmental samples. Images of scenes was recorded with CCD camera and decomposed in three RGB channels. The position, scale and rotation invariant image recognition was made through the scale transform. In all cases the bacteria was identified. The correlation peak positions that appear in green channel output are dependent of differences of bacterias angle (along y-axis) and size (along x-axis) in problem images with the filter image.

Identification of a red tide blooming species through an automatic optical-digital system

At present, a topic of great interest for the scientific community is to obtain an automatic monitoring system of red tide blooming organisms. The advances in automated monitoring systems have demonstrated that this automation is possible. In this paper, an analysis of the problems in the automated identification of red tide phytoplankton blooming is presented, using an automatic optical-digital system. Specifically, interclass size differences of organisms, different rotation and localization of the organisms in a microscope field and interclass of these same properties. The analysis was done automatically using a liquid crystal display device as interface of the digital with the optical part. This analysis is done for the first time in a hybrid system in real time.

Power cepstral image analysis through the scale transform

The detection of image changes irrespective on geometric transformations are required in many applications. In this paper we present a novel use of the scale transform oriented to image identification and registration. If we translate a signal then all the information appears in the phase of the Fourier transform of the translated signal. Similarly, if we scale or rotate an image all the information about the amount of scaling or rotation appear in the phase of the scale transform. In the present study we report a very precise image identification technique based on the use of the power cepstrum of the scale transform. Cepstral filtering can be considered as a non-linear adaptive prefilter followed by an autocorrelation operation. The accuracy of the cepstrum techniques and the speed of the Fourier transform makes the present method faster and more robust to noise than other existing techniques. Image registration has been accomplished by computing the power cepstrum of the log-polar scale mapping. The performance of the improved method has been experimentally verified in a class of typed characters and diatom images in lighting microscopy.

Fragmented fossil diatoms using an invariant correlation method

The taxonomic identification of diatom species that constituted phytoplankton communities in remote times is determining in several research fields like ecology, evolution, paleoecology and biostratigraphy. In the last 30 years the use of fossil diatoms like environmental indicators has become of prime importance. However, the use of these organisms is limited since they are found in sediment samples mostly fragmented or pulverized. This may lead to confusion and loss of information. In this work we used invariant correlation to identify 12 species of fossil diatoms. With this method we were able to identify the diatom species from only a small fragment of the organisms. This methodology can be used for the development of an automated system of plankton identification. An automatized identification of diatoms would be able to guarantee a faster identification of diatoms would be able to guarantee a faster identification and also would reduce the time necessary and also would reduce the time necessary for accomplishing analysis of samples highly fragmented.