Image Search and Retrieval

This paper presents a case study examining the utility of design exemplar technology as a search and retrieval tool with respect to retrieving mold inserts for a tire manufacturing company. Limitations of using the geometric-based exemplar approach such as tediousness of authoring exemplars and time complexity are identified. These limitations are addressed by developing a new parametric-based exemplar approach. This approach calculates a set of maxima and minima based on the specifications of the query mold insert. The design exemplar is essentially useful to prototype the query mechanism. However due to time complexity, the parametric approach was implemented as a dedicated software package.

Among the wide range of digital libraries, an interesting, yet quite neglected, subclass is constituted by those exclusively dealing with newspaper clippings. Compared with book–oriented digital libraries, clipping libraries are more difficult to seize, since they are wide and unstructured, and the subjects and content of a clipping are completely heterogeneous. LAURIN is an EU–funded project involving seventeen participants from several countries, including two software companies and a large group of libraries, whose main purpose is to set up a network of digitalized newspaper clipping archives that can be easily accessed through the Internet, for searching and retrieving clippings. The project also provides the libraries with models and methodologies to be used for scanning, digitalizing, storing, indexing, and making accessible newspaper clippings. This paper concentrates on the main architectural features of the LAURIN distributed system, exposing the peculiarities deriving from...

We introduced a real time Image Processing technique using modern programmable Graphic Processing Units (GPU) in this paper. GPU is a SIMD (Single Instruction, Multiple Data) device that is inherently data-parallel. By utilizing NVIDIA's new GPU Programming framework, " Compute Unified Device Architecture " (CUDA) as a computational resource, we realize significant acceleration in the computations of different Image processing Algorithms. Here we present an efficient implementation of algorithms on the NVIDIA GPU. Specifically, we demonstrate the efficiency of our approach by a parallelization and optimization of the algorithm. In result we show time comparison between CPU and GPU implementation.

Scope of the book:
This book focusses on the technical concepts of deep learning and its associated branch Neural Networks for the various dimensions of image processing applications. The proposed volume intends to bring together researchers to report the latest results or progress in the development of the above-mentioned areas. Since there is a deficit of books on this specific subject matter, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings.
Topics of Interest:
This book solicits contributions, which include the fundamentals in the field of Deep Artificial Neural Networks and Image Processing supported by case studies and practical examples. Each chapter is expected to be self-contained and to cover an in-depth analysis of real life applications of neural networks to image analysis.

More and more (semi) structured information is becoming available on the web in the form of documents embedding metadata (e.g., RDF, RDFa, Microformats and others). There are already hundreds of millions of such documents accessible and their number is growing rapidly. This calls for large scale systems providing effective means of searching and retrieving this semi-structured information with the ultimate goal of making it exploitable by humans and machines alike.This article examines the shift from the traditional web document model to a web data object (entity) model and studies the challenges faced in implementing a scalable and high performance system for searching semi-structured data objects over a large heterogeneous and decentralised infrastructure. Towards this goal, we define an entity retrieval model, develop novel methodologies for supporting this model and show how to achieve a high-performance entity retrieval system. We introduce an indexing methodology for semi-structured data which offers a good compromise between query expressiveness, query processing and index maintenance compared to other approaches. We address high-performance by optimisation of the index data structure using appropriate compression techniques. Finally, we demonstrate that the resulting system can index billions of data objects and provides keyword-based as well as more advanced search interfaces for retrieving relevant data objects in sub-second time.This work has been part of the Sindice search engine project at the Digital Enterprise Research Institute (DERI), NUI Galway. The Sindice system currently maintains more than 200 million pages downloaded from the web and is being used actively by many researchers within and outside of DERI.

Image similarity involves fetching similar looking images given a reference image. Our solution called SimNet, is a deep siamese network which is trained on pairs of positive and negative images using a novel online pair mining strategy inspired by Curriculum learning. We also created a multi-scale CNN, where the final image embedding is a joint representation of top as well as lower layer embedding's. We go on to show that this multi-scale siamese network is better at capturing fine grained image similarities than traditional CNN's.

Molten salt technology is a catchall phrase that includes some very diverse technologies; electrochemistry, heat transfer, chemical oxidation/reduction baths, and nuclear reactors. All of these technologies are linked by the general characteristics of molten salts that can function as solvents, have good heat-transfer characteristics, function like a fluid, can attain very high temperatures, can conduct electricity, and also may have chemical catalytic properties. The Janz molten salt database is the most comprehensive compilation of property data about molten salts available today and is widely used for both fundamental and applied purposes. Databases are traditionally viewed as “static” documents that are used in a “search and retrieval” mode. These static data can be transformed by informatics and data mining tools into a dynamic dataset for analysis of the properties of the, materials and for making predictions. While this approch has been successful in the chemical and biochemical sciences in searching for and establishing structure-property relationships, it is not widely used in the materials science community. Because the design of the original molten salt database was not oriented toward this informatics goal, it was essential to evaluate this dataset in terms of data mining standards. Two techniques were used—a projection (principal components analysis (PCA)) and a predictive method (partial least squares (PLS))—in conjunction with fundamental knowledge acquired from the long-term practice of molten salt chemistry.

Integrating Different Strategies for Cross-Language Information Retrieval in the MIETTA Project Paul Buitelaar, Klaus Netter, Feiyu Xu DFKI Language Technology Lab Stuhlsatzenhausweg 3, 66123 Saarbrücken, Germany {paulb, netter, feiyu}@ dfki. de ABSTRACT In this paper ...

Mei-Ling Shyu Department of Electrical and Computer Engineering University of Miami Coral Gables, FL 33124, USA 1-305-284-5566 shyu@miami.edu ... Shu-Ching Chen, Min Chen Distributed Multimedia Information System Laboratory School of Computer Science Florida ...

Summary Data intensive applications that rely heavily on huge databases waste a lot of time in searching and retrieval especially if there is a single server retrieving data from the database. This paper proposes a Beowulf cluster for fast query processing by distributing ...

A repository is a necessary prerequisite to support software engineers and other users in the process of developing software with and for reuse. In the literature, there are several works that explore reuse repositories, however their focus is mostly on reusable component search and retrieval issues, while important aspects of reuse repositories have not been properly explored. On the other hand, some questions raised by companies that desire to adopt or build a reuse repository remain unanswered. Such questions often include: What are the main roles and requirements of a reuse repository? What are the practical alternatives? How a reuse repository must be designed? Motivated by these questions, this paper presents a systematic approach with comparisons to existing tools and techniques for specifying, designing and implementing a reuse repository that was successfully constructed and deployed in real Brazilian software factories. Additionally, we describe the main design decisions, problems found, and future directions for research and development.

Social media websites like flickr and del. icio. us enable collaboration by allowing users to easily share content on the web through tagging. To provide a similar advantage to the enterprise, we have designed a tagging system for audio conversations. We are developing telephonic interfaces, where participants of a spoken conversation can opt to archive and share it. We have also developed a web-based visual interface that enables annotation, search, and retrieval of archived conversations. In this interface, we have ...

The paper focuses on the algorithms of the event detection in content-based video retrieval. Video has a complex structure and can express the same idea in different ways. This makes the task of searching for video more complicated. Video titles and text descriptions cannot give the whole information about objects and events in the video. This creates a need for content-based video retrieval. There is a semantic gap between low-level video features, that can be extracted, and the users’ perception. The task of event detection is reduced to the task of video segmentation. Complex content-based video retrieval can be regarded as the bridge between traditional retrieval and semantic-based video retrieval. The properties of video as a time series are described. Introduced the concept of anomalies in the video. A method for event detection based on comparing moving averages with windows of different sizes is proposed. According to the classification given at the beginning of this article, our method refers to statistical methods. It differs from other methods with low computational complexity and simplicity. The video stream processing language is proposed for function-based description of video handling algorithms. So, our method is formulated in the form of a declarative description on an interpreted programming language. Unfortunately, most of the existing video processing methods use exclusively imperative approach, which often makes understanding more difficult. Examples of the use of this language are given. Its grammar is described too. As shown by experiments, the implementation of the proposed video events retrieval method, unlike their counterparts, can work for video streams too with a real-time and potentially infinite frame sequences. Such advantages within low computational requirements make implementation of the method helpful in aviation and space technology. The algorithm has some disadvantages due to necessity parameter selection for particular task classes. The theorem on near-duplicates of video is formulated at the end of the article. It asserts the near-duplicate videos express the same sequence of phenomena.

The paper focuses on an overview of the different existing methods in content-based video retrieval. During the last decade there was a~rapid growth of video posted on the Internet. This imposes urgent demands on video retrieval. Video has a complex structure and can express the same idea in different ways. This makes the task of searching for video more complicated. Video titles and text descriptions cannot give the hole information about objects and events in the video. This creates a need for content-based video retrieval. There is a semantic gap between low-level video features, that can be extracted, and the users' perception. Complex content-based video retrieval can be regarded as the bridge between traditional retrieval and semantic-based video retrieval.

Keywords: frames; near-duplicates video; scenes; shots; video annotation; video classification; video mining; video reranking; video retrieval.

В статье предлагается обзор различных существующих методов ассоциативного поиска по видео. В течение прошлого десятилетия наблюдался стремительный рост количества видео размещаемых в Интернете, что создало острую необходимость в появлении поиска по видео. Видео имеет сложную структуру. Одна и та же информация может быть выражена различными способами. Это серьёзно усложняет задачу видео-поиска. Заголовки и описания видео не могут дать полного представления о самом видео, что влечет за собой необходимость использования ассоциативного поиска по видео. Существует семантический разрыв между низкоуровневыми характеристиками видео и восприятием пользователей. Комплексный ассоциативный видео-поиск может рассматриваться как связующее звено между обычным поиском и смысловым поиском по видео.

Ключевые слова: анализ видео; аннотирование видео; видео-поиск; кадры; классификация видео; нечеткие дубликаты видео; ранжирование видео; сцены; съёмки.