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‣ "Recuperação de imagens por conteúdo através de análise multiresolução por Wavelets" ; "Content based image retrieval through multiresolution wavelet analysis

Castañon, Cesar Armando Beltran
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 28/02/2003 Português
Relevância na Pesquisa
47.67378%
Os sistemas de recuperação de imagens por conteúdo (CBIR -Content-based Image Retrieval) possuem a habilidade de retornar imagens utilizando como chave de busca outras imagens. Considerando uma imagem de consulta, o foco de um sistema CBIR é pesquisar no banco de dados as "n" imagens mais similares à imagem de consulta de acordo com um critério dado. Este trabalho de pesquisa foi direcionado na geração de vetores de características para um sistema CBIR considerando bancos de imagens médicas, para propiciar tal tipo de consulta. Um vetor de características é uma representação numérica sucinta de uma imagem ou parte dela, descrevendo seus detalhes mais representativos. O vetor de características é um vetor "n"-dimensional contendo esses valores. Essa nova representação da imagem pode ser armazenada em uma base de dados, e assim, agilizar o processo de recuperação de imagens. Uma abordagem alternativa para caracterizar imagens para um sistema CBIR é a transformação do domínio. A principal vantagem de uma transformação é sua efetiva caracterização das propriedades locais da imagem. Recentemente, pesquisadores das áreas de matemática aplicada e de processamento de sinais desenvolveram técnicas práticas de "wavelet" para a representação multiescala e análise de sinais. Estas novas ferramentas diferenciam-se das tradicionais técnicas de Fourier pela forma de localizar a informação no plano tempo-freqüência; basicamente...

‣ Ambiente para avaliação de algoritmos de processamento de imagens médicas.; Environment for medical image processing algorithms assessment.

Santos, Marcelo dos
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 20/12/2006 Português
Relevância na Pesquisa
57.52092%
Constantemente, uma variedade de novos métodos de processamento de imagens é apresentada à comunidade. Porém poucos têm provado sua utilidade na rotina clínica. A análise e comparação de diferentes abordagens por meio de uma mesma metodologia são essenciais para a qualificação do projeto de um algoritmo. Porém, é difícil comparar o desempenho e adequabilidade de diferentes algoritmos de uma mesma maneira. A principal razão deve-se à dificuldade para avaliar exaustivamente um software, ou pelo menos, testá-lo num conjunto abrangente e diversificado de casos clínicos. Muitas áreas - como o desenvolvimento de software e treinamentos em Medicina - necessitam de um conjunto diverso e abrangente de dados sobre imagens e informações associadas. Tais conjuntos podem ser utilizados para desenvolver, testar e avaliar novos softwares clínicos, utilizando dados públicos. Este trabalho propõe o desenvolvimento de um ambiente de base de imagens médicas de diferentes modalidades para uso livre em diferentes propósitos. Este ambiente - implementado como uma arquitetura de base distribuída de imagens - armazena imagens médicas com informações de aquisição, laudos, algoritmos de processamento de imagens, gold standards e imagens pós-processadas. O ambiente também possui um modelo de revisão de documentos que garante a qualidade dos conjuntos de dados. Como exemplo da facilidade e praticidade de uso...

‣ BancoWeb: base de imagens mamográficas para auxílio em avaliações de esquemas CAD; Mammographic image database for CAD schemes evaluation

Matheus, Bruno Roberto Nepomuceno
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 22/04/2010 Português
Relevância na Pesquisa
57.31844%
Este trabalho teve como objetivo desenvolver uma base de imagens mamográficas online com acesso público para desenvolvimento, testes e avaliação comparativa de esquemas computadorizados de auxilio ao diagnóstico (CADs). A base contem imagens de vários hospitais, com grande variedade de laudos, também disponíveis na base assim como informações sobre dados clínicos (não confidenciais) dos pacientes. Uma interface detalhada foi criada para permitir o fácil acesso público, permitindo o uso de ferramentas de busca, recorte, analise estatística e inserção remota de imagens, entre outras. Testes comparativos com bases já existentes e amplamente usadas mostraram que a base desenvolvida tem quantidade e qualidade de imagens comparável ou superior as outras, além de oferecer uma quantidade de ferramentas muito maior.; This work has the objective of developing an online mamographic image database with public access for development, test and evaluation of computer-aided diagnosis (CAD). The database contains images from several hospitals, with great variety of medical reports, also available on the database together with other clinical information (not classified) from the patient. A detailed interface was developed to allow easy public access...

‣ Estudo comparativo de descritores para recuperação de imagens por conteudo na web; Comparative study of descriptors for content-based image retrieval on the web

Otavio Augusto Bizetto Penatti
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 13/03/2009 Português
Relevância na Pesquisa
47.582495%
A crescente quantidade de imagens geradas e disponibilizadas atualmente tem eito aumentar a necessidade de criação de sistemas de busca para este tipo de informação. Um método promissor para a realização da busca de imagens e a busca por conteúdo. Este tipo de abordagem considera o conteúdo visual das imagens, como cor, textura e forma de objetos, para indexação e recuperação. A busca de imagens por conteúdo tem como componente principal o descritor de imagens. O descritor de imagens é responsável por extrair propriedades visuais das imagens e armazená-las em vetores de características. Dados dois vetores de características, o descritor compara-os e retorna um valor de distancia. Este valor quantifica a diferença entre as imagens representadas pelos vetores. Em um sistema de busca de imagens por conteúdo, a distancia calculada pelo descritor de imagens é usada para ordenar as imagens da base em relação a uma determinada imagem de consulta. Esta dissertação realiza um estudo comparativo de descritores de imagens considerando a Web como cenário de uso. Este cenário apresenta uma quantidade muito grande de imagens e de conteúdo bastante heterogêneo. O estudo comparativo realizado nesta dissertação é feito em duas abordagens. A primeira delas considera a complexidade assinto tica dos algoritmos de extração de vetores de características e das funções de distancia dos descritores...

‣ The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

Armato, Samuel G.; McLennan, Geoffrey; Bidaut, Luc; McNitt-Gray, Michael F.; Meyer, Charles R.; Reeves, Anthony P.; Zhao, Binsheng; Aberle, Denise R.; Henschke, Claudia I.; Hoffman, Eric A.; Kazerooni, Ella A.; MacMahon, Heber; van Beek, Edwin J. R.; Yank
Fonte: U.S. Government Publicador: U.S. Government
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
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Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.

‣ A Visual Query-by-Example Image Database for Chest CT Images: Potential Role as a Decision and Educational Support Tool for Radiologists

Sasso, Giuseppe; Marsiglia, Hugo Raul; Pigatto, Francesca; Basilicata, Antonio; Gargiulo, Mario; Abate, Andrea Francesco; Nappi, Michele; Pulley, Jenny; Sasso, Francesco Silvano
Fonte: Springer-Verlag Publicador: Springer-Verlag
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
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Primary reading or further evaluation of diagnostic imaging examination often needs a comparison between the actual findings and the relevant prior images of the same patient or similar radiological data found in other patients. This support is of clinical importance and may have significant effects on physicians’ examination reading efficiency, service-quality, and work satisfaction. We developed a visual query-by-example image database for storing and retrieving chest CT images by means of a visual browser Image Management Environment (IME) and tested its retrieval efficiency. The visual browser IME included four fundamental features (segmentation, indexing, quick load and recall, user-friendly interface) in an integrated graphical environment for a user-friendly image database management. The system was tested on a database of 2000 chest CT images, randomly chosen from the digital archives of our institutions. A sample of eight heterogeneous images were used as queries and, for each of them a team of three expert radiologists selected the most similar images from the database (a set of 15 images containing similar abnormalities in the same position of the query). The sensitivity and the positive predictive factor, both averaged over the 8 test queries and 15 answers...

‣ Animal Detection in Natural Images: Effects of Color and Image Database

Zhu, Weina; Drewes, Jan; Gegenfurtner, Karl R.
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 10/10/2013 Português
Relevância na Pesquisa
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The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs) in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID) that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore...

‣ Food-pics: an image database for experimental research on eating and appetite

Blechert, Jens; Meule, Adrian; Busch, Niko A.; Ohla, Kathrin
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 24/06/2014 Português
Relevância na Pesquisa
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Our current environment is characterized by the omnipresence of food cues. The sight and smell of real foods, but also graphically depictions of appetizing foods, can guide our eating behavior, for example, by eliciting food craving and influencing food choice. The relevance of visual food cues on human information processing has been demonstrated by a growing body of studies employing food images across the disciplines of psychology, medicine, and neuroscience. However, currently used food image sets vary considerably across laboratories and image characteristics (contrast, brightness, etc.) and food composition (calories, macronutrients, etc.) are often unspecified. These factors might have contributed to some of the inconsistencies of this research. To remedy this, we developed food-pics, a picture database comprising 568 food images and 315 non-food images along with detailed meta-data. A total of N = 1988 individuals with large variance in age and weight from German speaking countries and North America provided normative ratings of valence, arousal, palatability, desire to eat, recognizability and visual complexity. Furthermore, data on macronutrients (g), energy density (kcal), and physical image characteristics (color composition...

‣ Combining multi-visual features for efficient indexing in a large image database

Ngu, A.; Sheng, Q.; Huynh, D.; Lei, R.
Fonte: Springer-Verlag Publicador: Springer-Verlag
Tipo: Artigo de Revista Científica
Publicado em //2001 Português
Relevância na Pesquisa
57.28363%
The optimized distance-based access methods currently available for multidimensional indexing in multimedia databases have been developed based on two major assumptions: a suitable distance function is known a priori and the dimensionality of the image features is low. It is not trivial to define a distance function that best mimics human visual perception regarding image similarity measurements. Reducing high-dimensional features in images using the popular principle component analysis (PCA) might not always be possible due to the non-linear correlations that may be present in the feature vectors. We propose in this paper a fast and robust hybrid method for non-linear dimensions reduction of composite image features for indexing in large image database. This method incorporates both the PCA and non-linear neural network techniques to reduce the dimensions of feature vectors so that an optimized access method can be applied. To incorporate human visual perception into our system, we also conducted experiments that involved a number of subjects classifying images into different classes for neural network training. We demonstrate that not only can our neural network system reduce the dimensions of the feature vectors, but that the reduced dimensional feature vectors can also be mapped to an optimized access method for fast and accurate indexing.; Anne H.H. Ngu...

‣ Using the Amazon Metric to Construct an Image Database based on what people do, not what they say.

Wyeld, Theodor G.; Colomb, R.M.
Fonte: IEEE Publicador: IEEE
Tipo: Conference paper
Publicado em //2006 Português
Relevância na Pesquisa
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Current image database metadata schemas require users to adopt a specific text-based vocabulary. Textbased metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat’s semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amozon.com returns other products also, based on an averaging of how users navigate the database. In this paper we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation...

‣ Organização automática de bancos de mamografias no padrão de densidade BI-RADS; Automatic organization of mammography database of the density patterns described in the BI-RADS

Rodrigues, Silvia Cristina Martini
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 30/08/2004 Português
Relevância na Pesquisa
47.48563%
Este trabalho apresenta um método computacional que classifica as mamografias no padrão de densidade BI-RADS, visando auxiliar a detecção precoce do câncer de mama, seja essa realizada por análise visual ou por auxílio computadorizado. A classificação das mamografias em bancos padronizados objetiva eliminar conflitos entre laudos mamográficos de diferentes profissionais, bem como quanto à conduta médica a ser seguida. Entretanto, o estabelecimento de bancos feito visualmente e principalmente em períodos diferentes dificulta sua uniformização, proporcionando uma classificação muito subjetiva e relativamente grosseira em conseqüência a grande variação entre e inter observadores. O método desenvolvido permitiu classificar as imagens independentemente da subjetividade própria à observação visual de quem organizou o banco ou da técnica de exposição aos raios X utilizada. Os resultados foram superiores a 92% mesmo para bancos de imagens totalmente diferentes. Esses resultados foram obtidos respeitando-se as possíveis diferenças de interpretações de diversas equipes médicas. Além do estabelecimento de banco de mamografias com limiares entre as composições bem quantificadas, com esta ferramenta, tanto os estagiários poderão ser treinados para classificar as imagens no padrão de densidades do BI-RADS...

‣ A non-expert organised visual database: a case study in using the Amazon metric to search images

Wyeld, Theodor G.
Fonte: IEEE Publicador: IEEE
Tipo: Conference paper
Publicado em //2007 Português
Relevância na Pesquisa
57.51206%
In a previous paper the notion of "using the Amazon metric to construct an image database based on what people do, not what they say" was introduced (see [1]). In that paper we described a case study setting where 20 participants were asked to arrange a collection of 60 images from most to least similar. We found they organised them in many different ways for many different reasons. Using Wexelblat's [2] semantic dimensions as axes for visualisation in conjunction with the Amazon metric we were able to identify common clusters of images according to expert and non-expert orderings. This second study describes the construction of a visual database based on the results of the first case study's non-expert participants' organising strategies and rationales. The same participants from the first study were invited to search for "remembered' images in the visual database. A better understanding was gained of their detailed reasonings behind their choices. This led to the development of a non-expert organised visual database that proved to be useful to the non-expert user. This paper concludes with some recommendations for future research into developing a non-expert, selforganising, visual, image database using multiple thesauri, based on these core studies.

‣ Boosting Manifold Ranking for image retrieval by mining query log repeatedly

Wu, J.; Shen, H.; Xiao, Z.B.; Wu, Y.B.; Li, Y.D.
Fonte: National Ilan University Publicador: National Ilan University
Tipo: Artigo de Revista Científica
Publicado em //2014 Português
Relevância na Pesquisa
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Manifold Ranking (MR) is one popular and successful technique for relevance feedback in content-based image retrieval (CBIR). However, existing MR methods have two main drawbacks. First, the affinity matrix used by MR is computed purely based on the visual features of images, which fails to accurately capture the semantic structure of image database. Second, the existing MR methods often suffer from the “cold start” problem where the feedback example set is quite small. In this paper, we propose a novel scheme that double exploits the query log in MR to address the drawbacks. In details, the correlation between each pair of database images is first estimated based on a query log, which serves to adjust the affinity matrix towards semantic structure. Then, the relevance score of each database image to the user’s query is further inferred from the query log, which could be used to produce more pseudo-labeled examples to handle the “cold start” problem. An empirical study shows that the proposed scheme is more effective than the state-of-the-art approaches.; Jun Wu, Hong Shen, Zhi-Bo Xiao, Yan-Bo Wu, Yi-Dong Li

‣ Glasgow's Stereo Image Database of Garments

Aragon-Camarasa, Gerardo; Oehler, Susanne B.; Liu, Yuan; Li, Sun; Cockshott, Paul; Siebert, J. Paul
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 28/11/2013 Português
Relevância na Pesquisa
47.48563%
To provide insight into cloth perception and manipulation with an active binocular robotic vision system, we compiled a database of 80 stereo-pair colour images with corresponding horizontal and vertical disparity maps and mask annotations, for 3D garment point cloud rendering has been created and released. The stereo-image garment database is part of research conducted under the EU-FP7 Clothes Perception and Manipulation (CloPeMa) project and belongs to a wider database collection released through CloPeMa (www.clopema.eu). This database is based on 16 different off-the-shelve garments. Each garment has been imaged in five different pose configurations on the project's binocular robot head. A full copy of the database is made available for scientific research only at https://sites.google.com/site/ugstereodatabase/.; Comment: 7 pages, 6 figure, image database

‣ Content-based image retrieval and its benefits for the stock photography market

Padeste, Romano
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Português
Relevância na Pesquisa
47.801514%
The development of powerful low-cost desktop computer systems has changed the pre-press business where tight deadlines must be met per sistently. An increasing number of newspapers and magazines are acquiring, handling, and storing images digitally while the use of hardcopies and slides decreases. Today's computers and high capacity storage-media enable stock pho tography agencies to build digital image databases, giving users fast access to large numbers of images. However, the transition from analog to digital image archives imposes new problems: with thousands of images at hand, the search for a particular image may turn into the search for the needle in a haystack. The first image Database Management Systems (DBMSs) were extended text DBMSs, which stored the image data along with a set of manually entered descriptive keywords. The major problem with this approach is that there is no generally agreed-upon language to describe images. Even sophis ticated DBMSs are unable to detect synonyms; hence, an image described with certain properties such as "curvy" may not be found if a user enters "wavy" as a search criterion. Furthermore, some image properties are hard to describe with keywords. A search is likely to fail if properties were not described at the database population stage when images are added to the database. Finally...

‣ Retrieval from an image knowledge base

Janicki, James
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Português
Relevância na Pesquisa
57.661616%
With advances in computer technology, images and image databases are becoming increasingly important. Retrievals of images in current image database systems have been designed using keyword searches. These carefully designed and handcrafted systems are very efficient given the application domain they are built for. Unfortunately, they are not adaptable to other domains, not expandable for other uses of the existing information and are not very forgiving to their users. The appearance of full-text search provides for a more general search given textual documents. However, pictorial images contain a vast amount of information that is difficult to catalog in a general way. Further this classification needs to be dynamic providing for flexible searching capability. The searching should allow for more than a pre-programmed set of search parameters, as exact searches make the image database quite useless for a search that was not designed into the original database. Further the incorporation of knowledge along with the images is difficult. Development of an image knowledge base along with content-based retrieval techniques is the focus of this thesis. Using an artificial intelligence technique called case-based reasoning, images can be retrieved with a degree of flexibility. Each image would be classified by user entered attributes about the image called descriptors. These descriptors would also have a "degree-of-importance" parameter. This parameter would indicate the relative importance or certainty of that descriptor. These descriptors are collected as the "case" for the image and stored in "frames" Each image can vary as to the amount of attribute information they contain. Retrieval of an image from the knowledge base begins with the entry of new descriptors for the desired image. Along with the descriptors are the degree-of-importance parameter. The degree-of-importance would indicate the requirement for the desired image to match that descriptor. Again...

‣ Cary collection web presentation & digital image database

McCombe, Cynthia
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Português
Relevância na Pesquisa
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The Melbert Cary, Jr. Graphic Arts Collection in the Wallace Memorial Library is one of the treasures the RIT community has had available for years. For this thesis project, selected materials from the collection were scanned and made available on the Internet so people at any location can experience the rare and invaluable items the facility houses. Not only has the result of this project created an educational tool for others to use, but it also challenged the author to master web publishing while developments rapidly occur on the most powerful mass communications media to arise in decades. While the primary purpose of this thesis project was to create an aesthetically pleasing and information rich web presentation for the Melbert Cary, Jr. Graphic Arts Collection, many secondary goals had to first be achieved. Those secondary goals are outlined in this list: 1. To acquire high quality color electronic images for others to access remotely. 2. To design a searchable database of 300 records. 3. To learn the ins-and-outs of web publishing by: Creating cohesive and consistent documents in the HyperText Markup Language (HTML). Developing an aesthetically pleasing interface for users to explore documents. This included keeping up-to-date with developments in HTML and using techniques created by web publishing experts to make the text as typographically pleasing as possible. Placing the necessary documents and images on a web server. Advertising the address of the presentation...

‣ Lippman 2000: a spectral image database under construction

Rosen, Mitchell; Jiang, Willie
Fonte: International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives Publicador: International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives
Tipo: Proceedings Formato: 661580 bytes; application/pdf
Português
Relevância na Pesquisa
67.55363%
In support of research projects both within the Munsell Color Science Laboratory and outside which rely on having full knowledge of the spectral makeup of scenes, a number of methods for capturing spectral images are being explored. This project is named Lippmann2000 in honor of Gabriel Lippmann who in 1891 devised a method to perfectly reconstruct the spectral content of real world scenes. In spite of Lippmann’s invention, a more primitive three-channel model, first demonstrated by James Clerk Maxwell 30 years prior, has dominated the color imaging field. The Maxwellian model, universal in today’s silver halide and electronic color image capture systems, relies on the metameric properties of the human visual system to simulate the appearance of an original color. It has been recognized by those in the forefront of imaging research that the capture of full spectral data holds advantage over traditional three-channel methods. This paper describes our efforts to-date to build our database of spectral images.; "Lippmann 2000: a spectral image database under construction," Presented at the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives. Chiba University. Held at Keyaki Hall, Chiba University...

‣ Using MPEG-7 to build a human brain image database for image-guided neurosurgery

Rege, Manjeet; Dong, Ming; Fotouhi, Farshad; Siadat, Mohammand-Reza; Zamorano, Lucia
Fonte: SPIE: SPIE International Symposium on Medical Imaging Publicador: SPIE: SPIE International Symposium on Medical Imaging
Tipo: Proceedings
Português
Relevância na Pesquisa
67.55363%
Multimedia annotation is domain specific and is assigned with the help of a domain expert to semantically enrich the data. These annotations are used for not only retrieval tasks but also to answer domain specific complex queries. To accomplish this, we propose to use MPEG-7 to annotate medical images and capture semantic information. In particular, we discuss the MPEG-7 based annotations for images of a human brain. Using MPEG-7, human brain images can be represented in an XML format. This MPEG-7 based XML file can be used to store the semantic medical information along with the low level features of the image We also present the database design to store and query the patient images for image-guided neurosurgery.; Copyright 2009 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.594638 …………………………………………………………………………………………………………………………………………………............................................. "Using MPEG-7 to build a human brain image database for image guided neurosurgery...

‣ COLOUR AND TEXTURE FEATURES FOR IMAGE RETRIEVAL IN GRANITE INDUSTRY

ÁLVAREZ,MARCOS J.; GONZÁLEZ,ELENA; BIANCONI,FRANCESCO; ARMESTO,JULIA; FERNÁNDEZ,ANTONIO
Fonte: DYNA Publicador: DYNA
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/03/2010 Português
Relevância na Pesquisa
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In this paper we study the feasibility of developing a search engine capable of retrieving images from a granite image database based on a query image that is similar to the intended targets. The main focus was on the determination of the set of colour and/or texture features which yields highest retrieval accuracy. To assess the performance of the considered image descriptors we created a granite image database, formed by images recorded at our laboratory as well as taken from the Internet. Experimental results show that colour and texture features can be successfully employed to retrieve granite images from a database. We also found that improved accuracy is achieved by combining different colour and texture feature sets through classifier fusion schemes.