本論文應用攝影構圖法則，以模糊邏輯理論為基礎，判別影像的攝影構圖類型。構圖(Composition)乃是攝影這項平面藝術創作最重要的美學元素之一，其目的是利用空間中的物體配置，經由透視投影後，讓畫面的整體呈現平衡感；專業的、優秀的攝影作品，皆會符合攝影的基本構圖原理。因此許多的影像增強、影像合成的應用中，也應該配合相片原本的構圖設計，針對所欲表達的重點予與適當地調整，而非「盲目的」以一體適用的法則去處理每一張照片。 論文中，我們針對影像所欲表達的重點區域，分析其結構特性，設計不同的特徵，並以模糊邏輯理論為基礎，應用Mamdani系統，結合隸屬函數與攝影構圖判別法則的交互作用，用以辨認所欲處理相片的構圖類別。依據辨認後的構圖類別，即可對該影像做適當地分割及調整，以使相片能有最佳的影像增強處理。 實驗證明，本文所提出的方法能有效地辨認攝影構圖類別，針對不同攝影構圖所作的影像修正，才能更符合人眼的視覺喜好。 / This thesis addresses the problem of how to recognize the photographic composition from a given photo based on the theory of fuzzy logic. Composition is one of the important aesthetics for the plane figure photo art. To present the balance of its holistic picture, it takes the advantage of special object arrangement after acting perspective projection. A piece of professional and qualified photo work will realize these basic photo composition methods. For many applications about the digital photo, the operations, i.e., photo enhancement, segmentation, output, and synthesis, all need to match up the photographic composition to do accurate processing rather than “blind” processing that assumes each photo with the same “composition.” An automatic recognition method using image features from some specific regions is described. The method is employed in a Mamdani model and combines outputs of multiple fuzzy logic rules and feature extraction algorithms to obtain confidences that can identify the correct photographic composition. Experimental results show that the proposed method is robust and effective for photographic composition recognition. The feature with adjusting in different photo composing will be able to comfort our human sight.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-17T13:42:57Z No. of bitstreams: 1 CLÁUDIO SABASTIÃO VASCONCELOS DA CUNHA CAVALCANTI - DISSERTAÇÃO PPGCC 2007..pdf: 19270985 bytes, checksum: b54c266f6cdb98e2cbbf305285b6ffdf (MD5) / Made available in DSpace on 2018-08-17T13:42:57Z (GMT). No. of bitstreams: 1 CLÁUDIO SABASTIÃO VASCONCELOS DA CUNHA CAVALCANTI - DISSERTAÇÃO PPGCC 2007..pdf: 19270985 bytes, checksum: b54c266f6cdb98e2cbbf305285b6ffdf (MD5) Previous issue date: 2007-07-30 / Além de ser uma das mais populares formas de arte, a fotografia também é uma forma de lazer e ferramenta de trabalho. Com a redução dos preços e a conseqüente popularização dos equipamentos e acessórios necessários à fotografia, especialmente o preço das câmeras digitais, é crescente o interesse por novos algoritmos e ferramentas que favoreçam a captura de imagens com maior qualidade. Diante do exposto, a presente dissertação objetivou a proposição e desenvolvimento de algoritmos capazes de detectar e corrigir falhas na composição fotográfica. As regras de composição fotográfica, em geral, são heurísticas utilizadas por fotógrafos que se difundiram a ponto de serem denominadas de “regras”. Mesmo não sendo consenso entre os fotógrafos, é possível que a implementação destas regras possa levar um fotógrafo amador, sem conhecimento prévio de fotografia, a produzir fotografias de alta qualidade e teor profissional. Neste trabalho são propostas duas alternativas para a correção da composição: um método para correção on-line, no qual a foto final só é obtida após satisfeitas algumas condições de qualidade, e outro para a correção off-line, o qual classifica (ou modifica) a imagem a posteriori. Para tanto, são utilizados algoritmos destinados à detecção e correção de problemas no posicionamento do tema. Os resultados foram avaliados em dois experimentos. No primeiro experimento, os usuários concordaram em até 65% com os resultados obtidos pelo sistema, através de uma análise subjetiva. No segundo experimento,foi mostrado como é possível, utilizando-se apenas uma câmera Pan-Tilt-Zoom (câmera dotada de três graus de liberdade sendo dois de rotação e um do campo de visão),localizar e fotografar pessoas em um determinado ambiente a partir das regras de composição desenvolvidas. / Besides being one of the most popular forms of art, photography is often used for a wide variety of purposes, including professional and entertainment ones. Nowadays, since cameras (specially digital ones) are less expensive and more popular, there is an increasing need for tools to help photographers (both amateurs and professionals) to obtain photographs of better quality. Within this context, algorithms for detection and correction of errors on the composition of a photograph are proposed in this work. Photographic composition rules are heuristics used by photographers, which became so wides pread that they are now also known as“rules”. Photographers, however, are not unanimous about the use of some of those rules. Despite of that it is possible that the use of photographic composition rules can improve the quality of amateur photographs, leveling them to a professional standard. In this dissertation, two approaches are proposed to automate composition rules: an on-line method, in which a picture is only taken when a number of conditions is satisfied; and an off-line method,which classifiers or corrects the image after it has been acquired. Hence, algorithms for detecting and correcting problems on subject positioning are used. Two experiments were used to evaluate the performance of the system. The first one shows that users agree with the correction performed on 65% of the photographs, through a subjective analysis. By using only a Pan-Tilt-Zoom camera and the composition rules implemented in this work, the second experiment shows howto locate and photograph human subjects ina given environment.

The goal of this work was to create an application providing the user with an option of creating interesting and realistic looking montages in few easy steps using a mobile phone. The focus is on simplicity, user friendliness and the speed with which the final montage can be obtained. The work discusses available approaches to building such application, the algorithms needed and also the problems with the implementation of computer vision algo- rithms on a mobile device. It also discusses possible options for speeding up the algorithms through parallelization on newer devices running the iOS operating system.