Estimativa do número de frutos verdes em laranjeiras com o uso de imagens digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudio comparativo de medidas de distancia para histogramas en problemas de reidentificación

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Localizzazione e riconoscimento di oggetti mediante descrittori locali

La tesi presenta un lavoro svolto nell'ambito dell'object recognition, in particolare riguardante l'analisi dei descrittori locali SIFT e BRIEF. Dopo aver implementato BRIEF, sono stati realizzati numerosi test al fine di presentare un esauriente confronto prestazionale tra i due descrittori. Infine, è stato realizzato un applicativo per la localizzazione e il riconoscimento di oggetti su ripiani.

Skin Lesion Extraction And Its Application

In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

A connectionist computational method for face recognition

In this work, a modified version of the elastic bunch graph matching (EBGM) algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM) framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.

Short stories by present-day authors,

- Stories of plot. (a) Dramatic incident:The red mark, John Russell. The Chink and the child, Thomas Burke. (b) Detective and mystery: The Doomdorf mystery, Melville Davisson Post. (c) Ingenuity and surprise: How it happened, A. Conan Doyle. (D) Problem: A jury of her peers, Susan Glaspell.- Stories of character. (a) Individual: Humoresque, Fannie Hurst. The game of life and death, Lincoln Colcord. (b) Psychological: The belled buzzard, Irvin Cobb.- Stories of setting. (a) Local color: The conversion of Elviny...

A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Uma interface para o controle de robôs móveis por intermédio de gestos

The main objective of this work was to enable the recognition of human gestures through the development of a computer program. The program created captures the gestures executed by the user through a camera attached to the computer and sends it to the robot command referring to the gesture. They were interpreted in total ve gestures made by human hand. The software (developed in C ++) widely used the computer vision concepts and open source library OpenCV that directly impact the overall e ciency of the control of mobile robots. The computer vision concepts take into account the use of lters to smooth/blur the image noise reduction, color space to better suit the developer's desktop as well as useful information for manipulating digital images. The OpenCV library was essential in creating the project because it was possible to use various functions/procedures for complete control lters, image borders, image area, the geometric center of borders, exchange of color spaces, convex hull and convexity defect, plus all the necessary means for the characterization of imaged features. During the development of the software was the appearance of several problems, as false positives (noise), underperforming the insertion of various lters with sizes oversized masks, as well as problems arising from the choice of color space for processing human skin tones. However, after the development of seven versions of the control software, it was possible to minimize the occurrence of false positives due to a better use of lters combined with a well-dimensioned mask size (tested at run time) all associated with a programming logic that has been perfected over the construction of the seven versions. After all the development is managed software that met the established requirements. After the completion of the control software, it was observed that the overall e ectiveness of the various programs, highlighting in particular the V programs: 84.75 %, with VI: 93.00 % and VII with: 94.67 % showed that the nal program performed well in interpreting gestures, proving that it was possible the mobile robot control through human gestures without the need for external accessories to give it a better mobility and cost savings for maintain such a system. The great merit of the program was to assist capacity in demystifying the man set/machine therefore uses an easy and intuitive interface for control of mobile robots. Another important feature observed is that to control the mobile robot is not necessary to be close to the same, as to control the equipment is necessary to receive only the address that the Robotino passes to the program via network or Wi-Fi.

Detecção de região saliente em imagens usando dissimilaridade de cor e amostragem por pixeis aleatórios

The purpose of this work is to demonstrate and to assess a simple algorithm for automatic estimation of the most salient region in an image, that have possible application in computer vision. The algorithm uses the connection between color dissimilarities in the image and the image’s most salient region. The algorithm also avoids using image priors. Pixel dissimilarity is an informal function of the distance of a specific pixel’s color to other pixels’ colors in an image. We examine the relation between pixel color dissimilarity and salient region detection on the MSRA1K image dataset. We propose a simple algorithm for salient region detection through random pixel color dissimilarity. We define dissimilarity by accumulating the distance between each pixel and a sample of n other random pixels, in the CIELAB color space. An important result is that random dissimilarity between each pixel and just another pixel (n = 1) is enough to create adequate saliency maps when combined with median filter, with competitive average performance if compared with other related methods in the saliency detection research field. The assessment was performed by means of precision-recall curves. This idea is inspired on the human attention mechanism that is able to choose few specific regions to focus on, a biological system that the computer vision community aims to emulate. We also review some of the history on this topic of selective attention.

Multicolor up conversion emission and color tunability in Yb3+/Tm3+/Ho3+ triply doped heavy metal oxide glasses

Multicolor and white light emissions have been achieved in Yb3+, Tm3+ and Ho3+ triply doped heavy metal oxide glasses upon laser excitation at 980 nm. The red (660 nm), green (547 nm) and blue (478 nm) up conversion emissions of the rare earth (RE) ions triply doped TeO2-GeO2-Bi2O3-K2O glass (TGBK) have been investigated as a function of the RE concentration and excitation power of the 980 nm laser diode. The most appropriate combination of RE in the TGBK glass host (1.6 wt% Yb2O3, 0.6 wt% Tm2O3 and 0.1 wt% Ho2O3) has been determined with the purpose to tune the primary colors (RGB) respective emissions and generate white light emission by varying the pump power. The involved infrared to visible up conversion mechanisms mainly consist in a three-photon blue up conversion of Tm3+ ions and a two-photon green and red up conversions of Ho3+ ions. The resulting multicolor emissions have been described according to the CIE-1931 standards. (C) 2011 Elsevier B.V. All rights reserved.

Mapping Individual Variation in Male Mating Preference Space: Multiple Choice in a Color Polymorphic Cichlid Fish

Sexual selection theory largely rests on the assumption that populations contain individual variation in mating preferences and that individuals are consistent in their preferences. However, there are few empirical studies of within-population variation and even fewer have examined individual male mating preferences. Here, we studied a color polymorphic population of the Lake Victoria cichlid fish Neochromis omnicaeruleus, a species in which color morphs are associated with different sex-determining factors. Wild-caught males were tested in three-way choice trials with multiple combinations of different females belonging to the three color morphs. Compositional log-ratio techniques were applied to analyze individual male mating preferences. Large individual variation in consistency, strength, and direction of male mating preferences for female color morphs was found and hierarchical clustering of the compositional data revealed the presence of four distinct preference groups corresponding to the three color morphs in addition to a no-preference class. Consistency of individual male mating preferences was higher in males with strongest preferences. We discuss the implications of these findings for our understanding of the mechanisms underlying polymorphism in mating preferences.

Self-supporting CVD diamond charge state conversion surfaces for high resolution imaging of low-energy neutral atoms in space plasmas

Two polycrystalline diamond surfaces, manufactured by chemical vapour deposition (CVD) technique, are investigated regarding their applicability as charge state conversion surfaces (CS) for use in a low energy neutral atom imaging instrument in space research. The capability of the surfaces for converting neutral atoms into negative ions via surface ionisation processes was measured for hydrogen and oxygen with particle energies in the range from 100 eV to 1 keV and for angles of incidence between 6 deg and 15 deg. We observed surface charging during the surface ionisation processes for one of the CVD samples due to low electrical conductivity of the material. Measurements on the other CVD diamond sample resulted in ionisation efficiencies of ~2 % for H and up to 12 % for O. Analysis of the angular scattering revealed very narrow and almost circular scattering distributions. Comparison of the results with the data of the CS of the IBEX-Lo sensor shows that CVD diamond has great potential as CS material for future space missions.