Wonder Alexandre Luz Alves
University of São Paulo
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Featured researches published by Wonder Alexandre Luz Alves.
brazilian symposium on computer graphics and image processing | 2010
Wonder Alexandre Luz Alves; Ronaldo Fumio Hashimoto
In this work we propose a method for localizing text regions within scene images consisting of two major stages. In the first stage, a set of potential text regions is extracted from the input image using residual operators (such as ultimate attribute opening and closing). In the second stage a set of features is obtained from each potential text region and this feature set will be later used as an input to a decision tree classifier in order to label these regions as text or non-text regions. Experiments performed using images from ICDAR public dataset show that this method is a good alternative for problems involving text location in scene images.
brazilian symposium on computer graphics and image processing | 2013
Wonder Alexandre Luz Alves; Alexandre Morimitsu; Joel Edu Sánchez Castro; Ronaldo Fumio Hashimoto
This work introduces a residual operator called ultimate attribute leveling. We also present an efficient algorithm for ultimate attribute leveling computation by using a structure called tree of shapes. Our algorithm for computating ultimate attribute leveling is based on the fact (proved in this work) that levelings can be obtained by pruning nodes from the tree of shapes. This is a novel result, since so far it is known that levelings can be obtained from component trees. Finally, we propose the use of ultimate attribute leveling with shape information to extract contrast using a priori knowledge of an application. Experimental results applied to text location show the potentiality of using ultimate attribute leveling with shape information for solving problems in image processing area.
international symposium on memory management | 2015
Wonder Alexandre Luz Alves; Alexandre Morimitsu; Ronaldo Fumio Hashimoto
This paper presents new theoretical contributions on scale-space representations based on levelings through hierarchies of level sets, i.e., component trees and tree of shapes. Firstly, we prove that reconstructions of pruned trees (component trees and tree of shapes) are levelings. After that, we present a new and fast algorithm for computing the reconstruction based on marker images from component trees. Finally, we show how to build morphological scale-spaces based on levelings through the reconstructions of successive pruning operations (whether based on increasing attributes or marker images).
international conference on image processing | 2014
Wonder Alexandre Luz Alves; Ronaldo Fumio Hashimoto
This work introduces a residual operator called ultimate grain filter which is a powerful image operator based on numerical residues. With a multi-scale approach, the ultimate grain filter analyzes an image under a series of grain filters of increasing grain sizes. Thus, contrasted objects can be detected if a relevant residue is generated when they are filtered out by one of these grain filters. We also present an efficient algorithm for ultimate grain filter computation by using a structure called tree of shapes. In fact, since the result of a given grain filter can be obtained by pruning the corresponding tree and reconstructing it, we show that the result of the ultimate grain filter (which is based on numerical residues from a family of grain filters) can be obtained by the computation of the difference (remaining nodes) of the corresponding pruned trees. Finally, we propose the use of ultimate grain filter to extract contrasted objects using a priori knowledge of an application.
Computers and Electronics in Agriculture | 2018
José Carlos Curvelo Santana; Sidnei Alves de Araújo; Wonder Alexandre Luz Alves; Peterson Adriano Belan; Ling Jiangang; Chen Jianchu; Liu Donghong
Abstract In this paper, the effects of vacuum cooling factors on the weight loss of postharvest broccoli were initially investigated. In sequence, the vacuum cooling treatment conditions were optimized using the response surface methodology (RSM) combined with the genetic algorithm (GA) technique. Fresh broccoli samples were harvested from a Chinese farm, and the green heads of selected samples were cut into smaller pieces, with diameters approximately 3–4 cm, and sequentially equilibrated to room temperature. Pressure (200–600 Pa), broccoli weight (200–500 g), water volume (2–6%, v/v) and time (20–40 min) were used as factors, and weight loss and end temperature were recorded as responses. The GA was employed to find the optimal condition for processing broccoli, and its initial solution was obtained from the RSM. The results demonstrate a good performance of the GA for the optimization of the broccoli cooling process. The best conditions of vacuum cooling process were as follows: a weight between 273.5 g and 278.0 g, a water volume of 3.0% v/v, a processing time of 40 min, a pressure of 200 Pa, and a weight loss and end temperature of 0.34 ± 0.01% and 2.0 ± 0.0 °C, respectively, leading to a percentage of profit of 99.66 ± 0.01%.
Journal of Intelligent Manufacturing | 2017
André Felipe Henriques Librantz; Sidnei Alves de Araújo; Wonder Alexandre Luz Alves; Peterson Adriano Belan; Rafael A. Mesquita; Antonio Henrique Pinto Selvatici
Plastic industry is today in a constant growth, demanding several products from other segments, which includes the plastic moulds, used mainly in the injection moulding process. This paper presents a methodology for the surface evaluation of plastic moulds, aiming the automation of the polishing surface analysis. Provided that this type of analysis by traditional procedures can be slow and expensive, the development of automatic system could lead to considerable improvements regarding the speed and reliability of information. The starting point of the evaluation procedure is the image generated by the laser light scattered over the sample mould surface that could be captured and analysed by image processing and artificial intelligence techniques. The results showed that the proposed system is able to mapping and classifying several damages over the polished surface and could be an alternative to reduce efficiently the costs and the spending time in mould surface inspection tasks.
Información tecnológica | 2012
Wonder Alexandre Luz Alves; Thiago Michel de Brito Farias; José Carlos Curvelo Santana
Se presenta la estrategia para desarrollada para la clasificacion sensorial de gelatinas obtenidas de patas de pollos utilizando redes neuronales basadas en los algoritmos de Kohonen. Estas redes muestran ser buenas herramientas para hacer las comparaciones sensoriales entre muestras, permitiendo identificar cuales son las mejores muestras entre las gelatinas. De acuerdo a los resultados la Gelatina D, con 3,80 % (m/v) de polvo de gelatina y 28,6 (m/v) de azucar fue a mejor entre las gelatinas de patas de pollo, recibiendo una aceptacion sensorial entre 6 y 8 puntos en la escala hedonica.
iberoamerican congress on pattern recognition | 2017
Charles F. Gobber; Wonder Alexandre Luz Alves; Ronaldo Fumio Hashimoto
This paper presents a filter based on energy functions applied to the ultimate levelings which are powerful image operators based on numerical residues. Within a multi-scale framework, these operators analyze a given image under a series of levelings. Thus, contrasted objects can be detected if a relevant residue is generated when they are filtered out by one of these levelings. During the residual extraction process, it is very common that undesirable regions of the input image contain residual information that should be filtered out. These undesirable residual regions often include desirable residual regions due to the design of the ultimate levelings which consider maximum residues. In this paper, we improve the residual information by filtering out residues extracted from undesirable regions. In order to test our approach, some experiments were conducted in plant dataset and the results show the robustness of our approach.
international conference on image analysis and recognition | 2016
Wonder Alexandre Luz Alves; Charles F. Gobber; Sidnei Alves de Araújo; Ronaldo Fumio Hashimoto
This paper proposes a method for segmentation of retinal blood vessels based on ultimate attribute opening (UAO). The proposed approach analyzes the space of numerical residues generated by UAO in order to select the residues extracted from elongated regions by means of an elongation shape descriptor. Thus, the residues extracted are used to define the ultimate elongation opening. Experimental results, using the public datasets DRIVE and STARE show that the proposed approach is fast, simple and comparable to other methods found in the literature.
Applied Mechanics and Materials | 2012
Wonder Alexandre Luz Alves; Sidnei Alves de Araújo; Jorge Henrique Pessota; Renato Augusto Barbosa O. Dos Santos
Sensory analysis has an important impact on food production since its results can help the understanding of consumers’ perceptions about the products. Thus, many methods have been proposed and applied to quantify sensory attributes of food products. In this paper we proposed a methodology, using Kohonens Self-Organizing Maps and K-means algorithm, to classify food samples through the responses, provided by human evaluators, for their attributes such as aroma, flavor, appearance and texture. Conducted experiments in sensory analysis to determine the acceptance of new gelatins produced from chicken feet and new wines produced from spares of Açaí and Cajá confirm that proposed methodology is suitable for the investigated purpose.