The environment is made up of composition of small particles. Hence, particle simulation is an important tool in many scientific and engineering research fields to simulate the real life processes of the environment. Because of the enormous amount of data in such simulations, data management, storage and processing are very challenging tasks. Spatial Distance Histogram (SDH) is one of the most popular queries being used in this field. In this thesis, we are interested in investigating the performance of improvement of an existing algorithm for computing SDH. The algorithm already being used is using a conceptual data structure called density map which is implemented via a quad tree index. An algorithm having density maps implemented via binary tree is proposed in this thesis. After carrying out many experiments and analysis of the data, we figure out that although the binary tree approach seems efficient in earlier stage, it is same as the quad tree approach in terms of time complexity. However, it provides an improvement in computing time by a constant factor for some data inputs. The second part of this thesis is dedicated to an approach that can potentially reduce the computational time to a great extent by taking advantage of regions where data points are uniformly distributed.

A method for real time tracking of non-rigid arbitrary objects is proposed in this study. The approach builds on and extends work on multidimensional color histogram based target representation, which is enhanced by spatial masking with a monotonically decreasing kernel profile prior to back-projection. The masking suppresses the influence of the background pixels and induces a spatially smooth target model representation suitable for gradient-based optimization. The main idea behind this approach is that an increase in the number of quantized feature spaces used to generate the target probability distribuition function during histogram back-projection can lead to improved target localization. Target localization is performed using the recursive Mean shift procedure, which climbs the underlying density graidients of the discrete data to find the mode (peak) of the distribution. Finally, the real time test cases, such as occlusion, target scale and orientation changes, varying illumination and background clutter, are demonstrated.

Aujourd’hui, des appareils capables de capter et de traiter les images peuvent être trouvés dans les systèmes complexes de surveillance ou de simples téléphones mobiles. Dans certaines applications, le temps nécessaire au traitement des images n’est pas aussi important que la qualité du traitement (par exemple, l’imagerie médicale). Par contre, dans d’autres cas, la qualité peut être sacrifiée au profit du facteur temps. Cette thèse se concentre sur ce dernier cas, et propose deux types de méthodes rapides pour l’amélioration du contraste d’image. Les méthodes proposées sont fondées sur l’égalisation d’histogramme (EH), et certaines s’adressent à des images en niveaux de gris, tandis que d’autres s’adressent à des images en couleur. En ce qui concerne les méthodes EH pour des images en niveaux de gris, les méthodes actuelles tendent à changer la luminosité moyenne de l’image de départ pour le niveau moyen de l´interval de niveaux de gris. Ce n’est pas souhaitable dans le cas de l’amélioration du contraste d’image pour les produits de l’électronique grand-public, où la préservation de la luminosité de l’image de départ est nécessaire pour éviter la production de distortions dans l’image de sortie. Pour éviter cet inconvénient, des méthodes de Biégalisation d’histogrammes pour préserver la luminosité et l’amélioration du contraste ont été proposées. Bien que ces méthodes préservent la luminosité de l’image de départ tout en améliorant fortement le contraste, elles peuvent produire des images qui ne donnent pas une impression visuelle aussi naturelle que les images de départ. Afin de corriger ce problème, nous proposons une technique appelée multi-EH, qui consiste à décomposer l’image en plusieurs sous-images, et à appliquer le procédé classique de EH à chacune d’entre elles. Bien que produisant une amélioration du contraste moins marquée, cette méthode produit une image de sortie d’une apparence plus naturelle. Nous proposons deux fonctions de décalage par découpage d’histogramme, permettant ainisi de concevoir deux nouvelle méthodes de multi-EH. Une fonction de coût est également utilisé pour déterminer automatiquement en combien de sous-images l’histogramme de l’image d’entrée sera décomposée. Les expériences montrent que nos méthodes sont meilleures pour la préservation de la luminosité et produisent des images plus naturelles que d´autres méthodes de EH. Pour améliorer le contraste dans les images en couleur, nous introduisons une méthode 5 Résumé 6 générique et rapide, qui préserve la teinte. L’égalisation d’histogramme est fondée sur l’espace couleur RGB, et nous proposons deux instantiations de la méthode générique. La première instantiation utilise des histogrammes 1D R-red, G-green, et B-bleu afin d’estimer l’histogramme 3D RGB qui doit être égalisé, alors que le deuxième instantiation utilise des histogrammes 2D RG, RB, et GB. L’égalisation d’histogramme est effectué en utilisant des transformations de décalage qui préservent la teinte, en évitant l’apparition de couleurs irréalistes. Nos méthodes ont des complexités de temps et d’espace linéaire, par rapport à la taille de l’image, et n’ont pas besoin de faire la conversion d’un espace couleur à l’autre afin de réaliser l’amélioration du contraste de l’image. Des évaluations objectives comparant nos méthodes et d’autres ont été effectuées au moyen d’une mesure de contraste et de couleur afin de mesurer la qualité de l’image, où la qualité est établie comme une fonction pondérée d’un indice de “naturalité” et d’un indice de couleur. Nous analysons 300 images extraites d’une base de données de l’Université de Berkeley. Les expériences ont montré que la valeur de contraste de l’image produite par nos méthodes est en moyenne de 50% supérieure à la valeur de contraste de l’image original, tout en conservant une qualité des images produites proche de celle des images originales / Nowadays devices are able to capture and process images from complex surveillance monitoring systems or from simple mobile phones. In certain applications, the time necessary to process the image is not as important as the quality of the processed images (e.g., medical imaging), but in other cases the quality can be sacrificed in favour of time. This thesis focuses on the latter case, and proposes two methodologies for fast image contrast enhancement methods. The proposed methods are based on histogram equalization (HE), and some for handling gray-level images and others for handling color images As far as HE methods for gray-level images are concerned, current methods tend to change the mean brightness of the image to the middle level of the gray-level range. This is not desirable in the case of image contrast enhancement for consumer electronics products, where preserving the input brightness of the image is required to avoid the generation of non-existing artifacts in the output image. To overcome this drawback, Bi-histogram equalization methods for both preserving the brightness and contrast enhancement have been proposed. Although these methods preserve the input brightness on the output image with a significant contrast enhancement, they may produce images which do not look as natural as the ones which have been input. In order to overcome this drawback, we propose a technique called Multi-HE, which consists of decomposing the input image into several sub-images, and then applying the classical HE process to each one of them. This methodology performs a less intensive image contrast enhancement, in a way that the output image presented looks more natural. We propose two discrepancy functions for image decomposition which lead to two new Multi-HE methods. A cost function is also used for automatically deciding in how many sub-images the input image will be decomposed on. Experimental results show that our methods are better in preserving the brightness and producing more natural looking images than the other HE methods. In order to deal with contrast enhancement in color images, we introduce a generic fast hue-preserving histogram equalization method based on the RGB color space, and two instances of the proposed generic method. The first instance uses R-red, G-green, and Bblue 1D histograms to estimate a RGB 3D histogram to be equalized, whereas the second instance uses RG, RB, and GB 2D histograms. Histogram equalization is performed using 7 Abstract 8 shift hue-preserving transformations, avoiding the appearance of unrealistic colors. Our methods have linear time and space complexities with respect to the image dimension, and do not require conversions between color spaces in order to perform image contrast enhancement. Objective assessments comparing our methods and others are performed using a contrast measure and color image quality measures, where the quality is established as a weighed function of the naturalness and colorfulness indexes. This is the first work to evaluate histogram equalization methods with a well-known database of 300 images (one dataset from the University of Berkeley) by using measures such as naturalness and colorfulness. Experimental results show that the value of the image contrast produced by our methods is in average 50% greater than the original image value, and still keeping the quality of the output images close to the original / Dispositivos para aquisição e processamento de imagens podem ser encontrados em sistemas complexos de monitoração de segurança ou simples aparelhos celulares. Em certas aplicações, o tempo necessário para processar uma imagem não é tão importante quanto a qualidade das imagens processadas (por exemplo, em imagens médicas), mas em alguns casos a qualidade da imagem pode ser sacrificada em favor do tempo. Essa tese se foca nesse último caso, e propõe duas metodologias eficientes para o realce de contraste de imagens. Os métodos propostos são baseados em equalização de histograma (EH), e focam em imagens em tons de cinza e em imagens coloridas. Os métodos baseados em EH atualmente utilizados para processar imagens em tons de cinza tendem a mudar o brilho médio da imagem para o tom médio do intervalo de tons de cinza. Essa mudança não é desejavél em aplicações que visam melhorar o contraste em produtos eletrônicos utilizados pelo consumidor, onde preservar o brilho da imagem original é necessário para evitar o aparecimento de artefatos não exitentes na imagem de saída. Para corrigir esse problema, métodos de bi-equalização de histogramas para preservação do brilho e contraste de imagens foram propostos. Embora esses métodos preservem o brilho da imagem original na imagem processada com um realce significante do contraste, eles podem produzir imagens que não parecem naturais. Esse novo problema foi resolvido por uma nova técnica chamada de Multi-Equalização de histogramas, que decompõe a imagem original em várias sub-imagens, e aplica o método de EH clássico em cada uma delas. Essa metodologia realiza um realce de contraste menos intenso, de forma que a imagem processada parece mais “natural”. Essa tese propõe duas novas funções de discrepância para decomposição de imagens, originando dois novos métodos de Multi-EH. Além disso, uma função de custo é utilizada para determinar em quantas sub-imagens a imagem original será dividida. Através da comparação objetiva e quantitative usando uma medida de constrate, os experimentos mostraram que os métodos propostos são melhores que outros EH estudados, uma vez que eles preservam o brilho e produzem imagens com uma aparência mais natural. Em relação aos métodos para realce de contraste em imagens coloridas, essa tese propõe um método genérico e eficiente de EH baseado no espaço de cores RGB que preserva o tom 9 Resumo 10 (a matiz), e implementa duas instâncias desse método genérico. A primeira instância utiliza os histogramas 1D R-red, G-green e B-blue para estimar um histograma 3D RGB, que é então equalizado. A segunda instância, por sua vez, utiliza os histogramas 2D RG, RB, e GB. A EH é executada utilizando transformadas de deslocamento que preservam a tonalidade da cor, evitando o aparecimento de cores não reais. Os métodos propostos tem complexidade linear no espaço e no tempo em relação ao tamanho da imagem, e não usam nenhuma conversão de um espaço de cores para outro. As imagens produzidas foram avaliadas objetivamente, comparando os métodos propostos com outros estudados. A avaliação objetiva foi feita utilizando medidas de contraste e de qualidade da cor da imagem, onde a qualidade foi definida como uma função ponderada dos índices de naturalidade e cromicidade. Um conjunto de 300 imagens extraídas da base de dados da Universidade de Berkeley foram analisadas. Os experimentos mostraram que o valor do contraste das imagens produzidas pelos métodos propostos é, em médias, 50% maior que o valor do contraste na imagem original, e ao mesmo tempo a qualidade das imagens produzidas é próxima a qualidade da imagem original / Dispositivi per l’acquisizione e lo svolgimento di immagini si possono trovare nei complessi sistemi di monitoramento di sicurezza o nei semplici cellulari. In alcune applicazioni il tempo necessario per svolgere un’immagine non è cosi importante come la qualità delle immagini svolte (es. nelle immagini mediche), ma in alcuni casi la qualità dell’immagine potrà venire daneggiata a favore del tempo. Questa tesi è basata su quest’ultimo caso e propone due metodi efficienti per evidenziare il contrasto di colore delle immagini. I metodi proposti vengono basate sull’equalizazzione d’istogramma (EI), mirati su delle immagini grigie e sulle immagini colorate. I metodi basati sull’EI attualmente utilizzati per svolgere delle immagini grigie tendono a cambiare il brillo medio dell’immagine per il tono medio dell’intervallo grigio. Questo cambiamento non è desiderato nelle applicazioni mirate al miglioramento del contrasto sui prodotti elettronici utilizzati dal consumatore, dove preservare il brillo dell’immagine originale è necessario per evitare la comparsa di artefatti inesistenti nell’immagine d’uscita. Sono stati proposti dei metodi di biequalizazzione di istogrammi per corregere questo problema della preservazione del brillo e del contrasto di colore delle immagini. Nonostante questi metodi preservino il brillo dell’immagine originale con significante rilievo del contrasto nell’immagine svolta, questi possono produrre delle immagini che non sembrino naturali. Questo nuovo problema è stato risolto con una nuova tecnica detta Multiequalizazzione di istogrammi, che decompone l’immagine originale in varie sottoimmagini, applicando su ognuna di queste il metodo EI classico. Questa metodologia realizza un contrasto di rilievo meno intenso in modo che l’immagine svolta sembri più “naturale”. Questa tesi propone due nuove funzioni di discrepanza per la decomposizione delle immagini, originandone due nuovi metodi Multi-EI. Inoltre una funzione di costo viene utilizzata per determinare in quante sottoimmagini l’immagine originale verrà divisa. Attraverso paragone obiettivo e quantitativo, usando una misura di contrasto, gli esperimenti hanno convalidato che i metodi proposti sono migliori di quegli EI studiati perché quelli preservano il brillo e producono immagini con un’apparenza più naturale. Con riferimento ai metodi utilizzati per rilevare il contrasto nelle immagini colorate questa tese propone un metodo generico ed efficiente di EI, in base negli spazi di colori 11 Risumo 12 RGB, che preserva il tono (la sfumatura) e implementa due istanze di questo metodo generico. La prima istanza utilizza gli istogrammi 1D R-Red, G-green e B-blue per stimare un istogramma 3D RGB, che viene di seguito equalizzato. La seconda istanza invece utilizza gli istogrammi 2D RG, RB e GB. La EI viene eseguita utilizzando trasformate di trasloco che preservano il tono del colore, evitando così la comparsa di colori non reali. I metodi proposti hanno complessità lineare nello spazio e nel tempo rispetto alla grandezza dell’immagine e non usano nessuna conversione da un spazio di colore all’altro. Le immagini prodotte sono state valutate in modo obiettivo, paragonando i metodi proposti con gli altri studiati. La valutazione obiettiva è stata fatta utilizzando delle misure di contrasto e qualità del colore dell’immagine, dove la qualità è stata definita come una funzione ponderata degli indici di naturalità e colorito. Si analisarano un insieme di 300 immagini tratte dalla base dei dati dell’Università di Berkeley. Gli sperimenti mostrarono che il valore del contrasto delle immagini prodotte daí metodi proposti è mediamente 50% maggiore del valore del contrasto nell’immagine originale e una volta ancora la qualità delle immagini prodotte è vicina alla qualità dell’immagine originale

Goal of this thesis is to propose and realize a viable method to determine static a dynamic parameters of GNSS receivers. Thesis begins with research of GNSS, foremostly determining position and associated uncertainties of measurement. Following chapter contains research of GNSS receivers, data flow and methods of evaluating parameters of such measurements. Summary of obtained information is then used to schedule measurements, assemble experiment and create evaluating metrics. Main selected evaluating metric is weighted histogram of deviations with extended information. Aplication of proposed metrics onto measurements of GNSS receivers augments available information of GNSS receiver accuracy for whole range of values. This metrics also supplies additional statistical information about course of measurement.

The diploma thesis is focused on histogram equalization method and his extension by the adaptive boundary. This thesis contains explanations of basic notions on that histogram equalization method was created. Next part is described the human vision and priciples of his imitation. In practical part of this thesis was created software that makes it possible to use methods of adaptive histogram equalization on real images. At the end is showed some results that was reached.

This master's thesis prepared the programme which is able to follow the trajectories of the movement of people and based on this to create various statistics. In practice it is an effective marketing tool which can be used for instance for customer flow analyses, optimal evaluation of opening hours, visitor traffic analyses and for a lot of other benefits. Histograms of oriented gradients, SVM classificator and optical flow monitoring were used to solve this problem. The method of multiple hypothesis tracking was selected for the association data. The system's quality was evaluated from the video footage of the street with the large concentration of pedestrians and from the school's camera system, where the movement in the corridor was monitored and the number of people counted.

This thesis deals with description of existing methods of image retrieval. It contains set of methods for image description, coding of global and local descriptor (SIFT, etc.) and describes method of effective searching in multidimensional space (LSH). It continues with proposal and testing of three global descriptors using color histograms, histogram of gradients and the combination of both. The last part deals with similar image retrieval using proposed descriptors and the indexing method LSH and compares the results with the existing method. Product of this work is an experimental application which demonstrates the proposed solution.

The task is to build an intelligent sensor that can instruct a Lego robot to perform certain tasks. The sensor is mounted on the Lego robot and it contains a digital camera which takes continuous images of the front view of the robot. These images are received by an FPGA which simultaneously saves them in an external storage device (SDRAM). At one time only one image is saved and during the time it is being saved, FPGA processes the image to extract some meaningful information. In front of digital camera there are different objects. The sensor is made to classify various objects on the basis of their color. For the classification, the requirement is to implement color image segmentation based object tracking algorithm on a small Field Programmable Gate array (FPGA). For the color segmentation in the images, we are using RGB values of the pixels and with the comparison of their relative values we get the binary image which is processed to determine the shape of the object. A histogram is used to retrieve object‟s features and saves results inside the memory of FPGA which can be read by an external microcontroller with the help of serial port (RS-232).

Reversible watermarking techniques extract the watermark and recover the original image losslessly from the watermarked image. They have been applied to those sensitive fields, such as the medicine and the military. Since an embedding pixel value may exceed the limitation of pixel value during the embedding process, most of the reversible watermarking methods require a location-map to record those pixels for recovering cover images. Although the location-map can be compressed by a lossless compression algorithm, and then embed into the watermarked image, this lowers embedding capacity and increases the complexity of watermarking during the procedures of embedding and extraction. In this thesis, we propose a reversible location-map free of watermarking algorithm. This algorithm first exploits the sorting and the correlation of neighboring pixels to increase the embedding capacity. Next we find thresholds from the predicted values. If the predicted value of an embedding pixel is within the thresholds, we can ensure that the pixel has no underflow or overflow problem during embedding process. Therefore, we can recover the cover image without any distortion. The experimental results reveal that the performance of our proposed method outperforms that proposed by FUJIYOSHI et al. For example, the embedding capacity obtained by the proposed method is higher than that obtained by FUJIYOSHI et al. about 60%, and the PSNR of our scheme is higher than FUJIYOSHI et al. about 5 dB.

Η διάδοση της χρήσης των υπολογιστών σε όλο και περισσότερους τομείς της καθημερινής μας ζωής, καθώς και η τεχνολογική εξέλιξη στην επιστήμη των υπολογιστών είχε σαν φυσικό επακόλουθο τη δημιουργία αλγορίθμων που έχουν στόχο την ανίχνευση και την αναγνώριση ανθρώπων με ακρίβεια καθώς και την παρακολούθηση τους. Τέτοιοι αλγόριθμοι εφαρμόζονται κυρίως σε συστήματα οπτικής επιτήρησης που είναι ζωτικής σημασίας σε διάφορους τομείς της καθημερινότητας. Αντικείμενο της παρούσας διπλωματικής εργασίας είναι η υλοποίηση ενός συστήματος ανίχνευσης, με τη χρήση του αλγόριθμου Histogram of Oriented Gradient (HOG), ταξινόμησης με χρήση Supported Vector Machines και παρακολούθησης ανθρώπου σε ακολουθία εικόνων, με χρήση αλγορίθμων υπολογιστικής όρασης όπως είναι ο αλγόριθμος φιλτραρίσματος σωματιδίων (Particle Filtering). / The widespread use of computers in more and more areas of our everyday life and the technological development in computer science as a natural consequence was the creation of algorithms that aim to detect and identify people accurately and monitor them. Such algorithms, are applied mainly in visual surveillance systems and is of vital importance in various areas of everyday life. The subject of this thesis is to implement a detection system using the algorithm Histogram of Oriented Gradient (HOG) as well, sort using Supported Vector Machines and the human tracking in image sequence, using computer vision algorithms such as Particle Filtering algorithm.