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

Contrast is an important factor in any subjective evaluation of image quality. It is the difference in visual properties that makes an object distinguishable from other objects and background. Contrast Enhancement method is mainly used to enhance the contrast in the image by using its Histogram. Histogram is a distribution of numerical data in an image using graphical representation. Histogram Equalization is widely used in image processing to adjust the contrast in the image using histograms. Whereas Gamma Correction is often used to adjust luminance in an image. By combining Histogram Equalization and Gamma Correction we proposed a hybrid method, that is used to modify the histograms and enhance contrast of an image in a digital method. Our proposed method deals with the variants of histogram equalization and transformed based gamma correction. Our method is an automatically transformation technique that improves the contrast of dimmed images via the gamma correction and probability distribution of luminance pixels. The proposed method is converted into an android application. We succeeded in enhancing the contrast of an image by using our method and we have tested for different alpha values. Graphs of the gamma for different alpha values are plotted.

In public education, it is not possible to present school programs that will satisfy all the external groups from society. When an outside interest group perceives a need that is lacking in the schools' curriculum, it may petition the ministry of education or the local school board to include its need into the curricula. Another method to influence or insert its point of view is for the interest group to produce its own curriculum for a school program. This study investigated the impact of one outside interest group as it attempts to modify students' attitudes through its school program, Salmonids in the Classroom. Werner's description of editorial criticism permitted examination with a political perspective, of the resource package, Salmonids in the Classroom. The methodology of this analysis permitted a view of the goals and values espoused and hidden in a school program and how those goals and values were modified as they are passed from the program sponsors through the developers to the teachers. To determine the effects of the Salmonids in the Classroom Program upon student attitudes toward the salmonid resource, a Likert-type instrument using a slide show was used. To understand children's beliefs and attitudes about the salmonid resource, student interviews were conducted with some students after they were exposed to the Salmonids in the Classroom Program. This study confirms that a special interest group can sponsor a school program and modify student attitudes to be more supportive of the interest group's programs and goals. This study may be useful not only to teachers to assist in clarifying their role with the special interest group's school program, but it may also be useful to special interest groups who may be planning ways to influence the public through the school system. / Education, Faculty of / Curriculum and Pedagogy (EDCP), Department of / Graduate

This paper introduced a Computer-Aided Optically Scanned Document Information Extraction System. It could extract information including invoice No., issued date, buyer, etc., from the optically scanned document to meet the demand of customs declaration companies. The system output the structured information to a relational database. In detail, a software architecture for the information extraction of diverse-structure optically scanned document is designed. In this system, the original document is classified firstly. It would put into template-based extraction to improve the extraction performance if its template is pre-defined in the system. Then, a method for image enhancement to improve the image classification is proposed. This method aims to optimize the accuracy of neural network model by extracting the template-related feature and actively removing the unrelated feature. Lastly, the above system is implemented in this paper. This extraction are programed in Python which is a cross-platform languages. This system comprises three parts, classification module, template-based extraction and non-template extraction all of which have APIs and could be ran independently. This feature make this system flexible and easy to customization for the further demand. 445 real-world customs document images were input to evaluate the system. The result revealed that the introduced system ensured the diverse document support with non-template extraction and reached the overall high performance with template-based extraction showing the goal was basically achieved.

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Much of the current literature related to injuries in sport has addressed the influence of a particular exercise intervention on a specific type of injury without considering changes in sport performance. The purpose of this research was to investigate an interdisciplinary approach to athlete development and its initial effects on injury rates and measures of performance in collegiate baseball. In October 2008, an NCAA Division I baseball team began working with a sport performance enhancement group (SPEG) which consists of a collaborative effort between sport coaches, sport medicine and sport science departments. Injury rates were calculated for each academic year from 2006/2007 through 2010/2011. As part of the athlete monitoring program provided through SPEG, peak force was measured using an isometric mid-thigh pull from 2008/2009 through 2010/2011. Team win percentage and home runs were also reported from 2003/2004 through 2010/2011. Compared to 2006/2007 and 2007/2008, injury rates during 2008/2009 decreased 40% and 16%, 2009/2010 decreased 64% and 48%, while 2010/2011 decreased 33% and 6%. Team mean allometrically scaled isometric peak force (IPFa) increased each year from 2008/2009 through 2010/2011 (200.6 N, 229.6 N, 244.2 N). IPFa during 2009/2010 and 2010/2011 were significantly greater than 2008/2009 (p = .001 and .002). Win percentage increased from 2008/2009 through 2010/2011 (47%, 53%, 63%) and the 2010/2011 win percentage was higher than any other year since 2003/2004. Total team home runs during 2009/2010 and 2010/2011 were higher than any other season since 2003/2004. These results seem to indicate that the collaborative efforts of SPEG were able to substantially reduce injury rates while increasing lab based and on-field performance.

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京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第22743号 / 医博第4661号 / 新制||医||1046(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 花川 隆, 教授 渡邉 大, 教授 黒田 知宏 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23160号 / 工博第4804号 / 新制||工||1751(附属図書館) / 京都大学大学院工学研究科分子工学専攻 / (主査)教授 関 修平, 教授 今堀 博, 教授 梶 弘典 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM