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For the images of an objects with multi-viewpoints, the visual words in a visual phrase may be covered by the object and thus degrades the visual phrase extraction performance. This paper presents an approach to robust visual phrase extraction using graph mining for content-based image retrieval. In this study, the concurrent appearance of two visual words can be estimated over all of the category-related...
The following papers are dealt with: software component verification; decision support system; web service; ERP; SQL; semantic data gathering; network security; software development; knowledge-based environmental information system; artificial neural network based radial bending; graph theory model; ontology-based process model; data mining; rough-neuro fuzzy network; feature extraction; query processing;...
This paper presents 2D shape matching technique using hierarchical tree structure extracted from shock graph that in turn extracted from the skeleton of the shape of interest. Object recognition and shape matching are important issues in the field of image processing. Extraction and application of skeleton of a shape is widely used in these fields. In this paper shape representation, matching and...
Content-based image retrieval (CBIR) considers the characteristics of the image itself, for example its shapes, colors and textures. The current approaches to CBIR differ in terms of which image features are extracted. Recent work deals with combination of distances or scores from different and independent representations. This work attempts to induce high level semantics from the low level descriptors...
A new geometric constraints histogram descriptor (GCHD) based on curvature mesh graph for image retrieval is presented in this paper. Through this method, the edge and angle geometric constraints based on the curvature mesh graph are extracted firstly. Then the histogram algorithm is applied on the geometric constraints to obtain the histogram matrix for each curvature point. Finally, the histograms...
Ranking is a crucial task in information retrieval systems. This paper proposes a novel ranking model named WIRank, which employs a layered genetic programming architecture to automatically generate an effective ranking function, by combining various types of evidences in Web image retrieval, including text information, image-based features and link structure analysis. This paper also introduces a...
Medical image features extraction is a crucial part in medical image retrieval system. In order to extract the medical image feature more accurately for improving the retrieval efficiency, a sort of novel feature called rdquofrequency layer featurerdquo and a method used for extracting the feature were proposed in this paper. First, the image was decomposed several sub-images in different frequency...
Image annotation has been an active research topic in recent years. However, the state of art image annotation methods are often unsatisfactory, in this paper, we presented a novel image annotation refinement to improve the performance of automatic image annotation. Firstly, the initial pair-wise similarities of words is computed based on the co-occurrence of training sets, Then the topic relation...
Automatic annotation of digital pictures is a key technology for managing and retrieving images from large image collections. Typical algorithms only deal with the problem of monolingual image annotation. In this paper, we propose a framework to deal with the problem of multilingual image annotation, which can annotate images in multiple languages. The framework can not only benefit users with different...
In this paper a region-based image indexing and retrieval (RBIR) algorithm is presented. As a basis for the indexing, a novel spectral segmentation approach using random walks on graphs is introduced. Based on the extracted regions, characteristic features are estimated using color and texture information. The focus of this study is to improve the capture of regions so as to enhance indexing and retrieval...
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