1,720,969 research outputs found
An Investigation in Image Retrieval for Analysing Welding Defects
No full textThe development of new approaches in image processing
and retrieval provides several opportunities in supporting
in different domains. The group of welding engineers frequently
needs to conduct visual inspections to assess the quality
of weldings. It is investigated, if this process can be supported
by different kinds of software. A generic CBIR system
has been successfully used to sort welding photographs
according to the severity of visual faults. Similar algorithms
were used to automatically spot and measure the diameter of
gas pores
An Investigation in Applying Image Retrieval Techniques to X-Ray Engineering Pictures
No full textUsing image retrieval techniques in analysing Non-destructive testing reults is a new challenge in both
computing science and engineering applications. Objective of this research is to develop an image retrieval system
to analyse X-ray images for welding industry. The content based image retrieval has been used in this investigation,
particularly in feature vector paradigm and similarity as well as detailed analysis towards single defects. It is found
that X-ray images can be digitally analysed qualitatively and quantitatively easily. It concludes that the use of
existing CBIR techniques can provide a platform to quickly develop new image analysis tools
An Extensible Query Language for Content Based Image Retrieval
No full textOne of the most important bits of every search engine is the query interface. Complex interfaces may cause users to struggle in learning the handling. An example is the query language SQL. It is really powerful, but usually remains hidden to the common user. On the other hand the usage of current languages for Internet search engines is very simple and straightforward. Even beginners are able to find relevant documents.
This paper presents a hybrid query language suitable for both image and text retrieval. It is very similar to those of a full text search engine but also includes some extensions required for content based image retrieval. The language is extensible to cover arbitrary feature vectors and handle fuzzy queries
Semi-Supervised Image Classification based on a Multi-Feature Image Query Language
No full textThe area of Content-Based Image Retrieval (CBIR) deals with a wide range of research disciplines. Being closely related to text retrieval and pattern recognition, the probably most serious issue to be solved is the so-called \semantic gap". Except for very restricted use-cases, machines are not able to recognize the semantic content of digital images as well as humans.
This thesis identifies the requirements for a crucial part of CBIR user interfaces, a multimedia-enabled query language. Such a language must be able to capture the user's
intentions and translate them into a machine-understandable format. An approach to tackle this translation problem is to express high-level semantics by merging low-level image features. Two related methods are improved for either fast (retrieval) or accurate(categorization) merging.
A query language has previously been developed by the author of this thesis. It allows the formation of nested Boolean queries. Each query term may be text- or content-based and the system merges them into a single result set. The language is extensible by arbitrary new feature vector plug-ins and thus use-case independent.
This query language should be capable of mapping semantics to features by applying machine learning techniques; this capability is explored. A supervised learning algorithm based on decision trees is used to build category descriptors from a training set. Each resulting \query descriptor" is a feature-based description of a concept which is comprehensible and modifiable. These descriptors could be used as a normal query and return a result set with a high CBIR based precision/recall of the desired category. Additionally, a method for normalizing the similarity profiles of feature vectors has been
developed which is essential to perform categorization tasks.
To prove the capabilities of such queries, the outcome of a semi-supervised training session with \leave-one-object-out" cross validation is compared to a reference system. Recent work indicates that the discriminative power of the query-based descriptors is similar and is likely to be improved further by implementing more recent feature vectors
Semi-supervised image classification based on a multi-feature image query language
Get PDFThe area of Content-Based Image Retrieval (CBIR) deals with a wide range of research disciplines. Being closely related to text retrieval and pattern recognition, the probably most serious issue to be solved is the so-called \semantic gap". Except for very restricted use-cases, machines are not able to recognize the semantic content of digital images as well as humans. This thesis identifies the requirements for a crucial part of CBIR user interfaces, a multimedia-enabled query language. Such a language must be able to capture the user's intentions and translate them into a machine-understandable format. An approach to tackle this translation problem is to express high-level semantics by merging low-level image features. Two related methods are improved for either fast (retrieval) or accurate(categorization) merging. A query language has previously been developed by the author of this thesis. It allows the formation of nested Boolean queries. Each query term may be text- or content-based and the system merges them into a single result set. The language is extensible by arbitrary new feature vector plug-ins and thus use-case independent. This query language should be capable of mapping semantics to features by applying machine learning techniques; this capability is explored. A supervised learning algorithm based on decision trees is used to build category descriptors from a training set. Each resulting \query descriptor" is a feature-based description of a concept which is comprehensible and modifiable. These descriptors could be used as a normal query and return a result set with a high CBIR based precision/recall of the desired category. Additionally, a method for normalizing the similarity profiles of feature vectors has been developed which is essential to perform categorization tasks. To prove the capabilities of such queries, the outcome of a semi-supervised training session with \leave-one-object-out" cross validation is compared to a reference system. Recent work indicates that the discriminative power of the query-based descriptors is similar and is likely to be improved further by implementing more recent feature vectors.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Design
No full textIn this chapter, a CBIR design based on previous work of the author (Pein, 2008) is presented. The available system already allows for a retrieval by a query string (Pein, Lu, & Renz, 2008a). In the context of this investigation, the system has been extended to support alternative user interfaces as well as a testing module used in the case studies below. Being a pure research prototype, the retrieval engine is optimized for generating accurate results in order to have a reliable data foundation. Further, the query language syntax and the constraints for a practical application of the learning algorithm are presented.AlternativeReviewe
Content based image retrieval by combining features and query-by-sketch
No full textThis paper reports an approach to improve content-based image retrieval systems. Most
current systems are based on a single technique for feature extraction and similarity search.
Each technique has its advantages and drawbacks concerning the result quality. Usually they
cover one or two certain features of the image, e.g. histograms or shape information. To
overcome these restrictions a flexible framework is proposed, capable of combining several
different features in a single retrieval system. This system allows an administrator to build
a repository managing different feature vectors. A user searching through this repository
defines and weights these features according to his needs in the query. It concludes that a
combined retrieval can be used much more widely than a highly specialized one and the use
of query-by-sketch or -example combined with semantic information (e.g. keywords) could
enhance the result quality
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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