The objective of this paper is to present the results of a class developed with routines in Java language, and contribution of OpenCV library, for analysis and extraction of metadata from images. To evaluate the developed class, three different figures were produced in cardstock and their perimeters were measured with a millimeter ruler. Then these figures were scanned for further image analysis with aid of the developed class. The images of the figures were initially saved in BMP format. After it, each of the images in BMP format were saved in JPG and PNG file formats resulting, at the end, on nine images. The validation of the correct extraction of the image metadata and so the perimeter value of the object was performed by comparing the values obtained by direct measurement perimeter of the figure, with a millimeter ruler, and the values obtained with digital image processing, counting the contour pixels of the image of the figure, and using the image resolution, one of the extracted metadata. For the edge detection and counting of the contour pixels of object, the algorithms cvFindContours() and cvContourPerimeter(), of OpenCV library, were used. It was obtained, for the worst case, a percentage error of 8.0 %, for images with BMP and PNG format. Therefore, the developed class presents satisfactory results and is recommended to extract and calculate measures of an object present in the image.
The evaluation of the root system is important for better understanding the effects of nutrient management on soil and plant nutri-tion. However, root system studies and culture are slow and show low accuracy. In this context, digital image processing may be an alternative. The objective of this research was to develop a computational method to assist evaluation of the soybean root growth. Initially, the free and open access software, available at: http://rm.deinfo.uepg.br/, was developed in Java platform with the OpenCV library supply through the plug-in JavaCV. To evaluate the software, copper wires with 10 mm, 20 mm, and 50 mm of length manually measured using callipers. They were scanned with a resolution of 300 dpi and then images were loaded in the software. Variation coefficients between 0.01 and 2.99 % were obtained. Subsequently, the samples of soybean roots were scanned and the results of developed software and Safira software were correlated with those from the line-intersect method. The determination coefficients (R² = 0.999) of the developed software, on average, were better than those obtained with Safira software (R² = 0.733), when compar-ing with the line-intersect method. Therefore, the proposed method was accurate for length measurements of soybean roots.
The evaluation of root crops is important for better understanding of the effects of plant nutrition and nutrient management in the soil. However, the studies and the root system of the culture are slow, require a long time and show low precision results. In this context, digital image processing can be an alternative. The objective of this study was to develop a computational method to assist in the evaluation of the surface area of soybean roots. It was initially developed in Java platform by providing the OpenCV library through the plug-in JavaCV. Then, after the manual count, the soybean root samples that have been scanned, were loaded into the software. The software developed results were correlated with the intersection of the line method. The correlation coefficient (R = 0.77) obtained by the software developed was on average good, compared to the métododa line intersection. Therefore, in general, the proposed method was necessary paraestimar the surface area of the soybean roots.
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