This work presents a new technique as a potential methodology to analyse seeds. The technology is known as dynamic speckle, or biospeckle, an optical phenomenon produced when active materials, such as biological tissue, are illuminated by laser light. In the present work, the biological activity of seed tissues has been inferred from quantitative and qualitative measurements of their speckle activity. The aim is to show that the biospeckle technique has a potential as a methodology to assess seed viability. One aspect that needs to be investigated is how the water content in the seeds affects bio speckle activity. An experiment has been performed to determine the effect of humidity in the results. Seed activity for different levels of humidity was determined using quantitative and qualitative methods. Also, in others experiments, viable and non viable seeds with different specific humidity levels could be classified using the same technique. £)

This work presents a study of a new technology applied in quality tests of oranges. Evaluations were performed using a nondestructive and noninvasive method based on the interpretation of an optical phenomenon that occurs when the fruit is illuminated with coherent light, referred as biospeckle. The speckle patterns of laser light scattered in orange fruits have been measured through their quantification. For the quantification of the variation by biospeckle, the autocorrelation function and the modified occurrence matrix were used. From these functions, two parameters were obtained: the statistical cummulant and the moment of inertia, calculated from the modified occurrence matrix. These values were used as quality and senescence indicators for the specimens and were compared with other parameters, as total soluble solids, total acidity, the penetration force and the storage period. It was observed that the moment of inertia and statistical cummulant decrease during the storage period. Since senescence is dependent on the storage period, it was possible to observe that the measure of the dynamic speckle varies for fruits as their quality decrease, and also the values change with the position where the images are taken.

Vegetable quality is frequently referred to size, shape, mass, firmness, color and bruises from which fruits can be classified and sorted. However, technological by small and middle producers implementation to assess this quality is unfeasible, due to high costs of software, equipment as well as operational costs. Based on these considerations, the proposal of this research is to evaluate a new open software that enables the classification system by recognizing fruit shape, volume, color and possibly bruises at a unique glance. The software named ImageJ, compatible with Windows, Linux and MAC/OS, is quite popular in medical research and practices, and offers algorithms to obtain the above mentioned parameters. The software allows calculation of volume, area, averages, border detection, image improvement and morphological operations in a variety of image archive formats as well as extensions by means of "plugins" written in Java.Key words: fruits and vegetables selection, ImageJ software, machine vision. RESUMO TÉCNICA DE PROCESSAMENTO DE IMAGEM PARA CLASSIFICAÇÃO DE LIMÕES E TOMATESA qualidade vegetal freqüentemente se refere a tamanho, forma, massa, firmeza, cor e danos, em que podem ser classificados e ordenados. Porém, sua implementação tecnológica se torna inviável, para pequenos e médios produtores, devido ao alto custo de softwares, equipamentos, além dos custos operacionais. Com base nessas considerações, a proposta deste trabalho é estudar a adaptação de um novo software, com código-fonte aberto para habilitar o sistema de classificação reconhecendo forma, volume, cor e possivelmente danos. O software chamado ImageJ, compatível com o Windows, Linux e MAC/OS, é bastante popular em práticas e pesquisas médicas, e oferece algoritmos para obter os parâmetros mencionados acima. Entre os recursos oferecidos pelo pacote destaca-se a disponibilidade de diversos algoritmos com código-fonte abertos para: manipulação dos mais variados formatos de arquivo de imagens, detecção de bordas, melhoria de imagens, cálculos diversos (áreas, médias, centróides) e operações morfológicas. Este software disponibiliza também um ambiente gráfico que simplifica a utilização de tais recursos, além de permitir a extensão através de "plugins" escritos em Java.Palavras-chave: seleção de frutas e hortaliças, software ImageJ, visão de máquina.