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With the advent of multimedia computer, the voice and images could be stored in database. How to retrieve the information user want is a heard question. To query the large numbers of digital images which human desired is not a simple task. The studies of traditional image database retrieval use color, shape, and content to analyze a digital image, and create the index file. But they cannot promise that use the similar index files will find the similar images, and the similar images can get the similar index files. In this thesis, we propose a new method to analyze a digital image by fractal code. Fractal coding is an effective method to compress digital image. In fractal code, the image is partitioned into a set of non-overlapping range blocks, and a set of overlapping domain blocks is chosen from the same image. For all range blocks, we need to find one domain block and one iteration function such that the mapping from the domain block is similar to the range block. Two similar images have similar iterated functions, and two similar iterated functions have similar attractors. In these two reasons, we use the iteration function to create index file. We have proved fractal code can be a good index file in chapter 3. In chapter 4, we implement the fractal-based image database. In this system, we used fractal code to create index file, and used Fisher discriminate function, color, complexity, and illumination to decide the output order.

A symbolic image database system is a system in which a large amount of image data and their related information are represented by both symbolic images and physical images. How to perceive spatial relationships among the components in a symbolic image is an important criterion to find a match between the symbolic image of the scene object and the one being store as a modal in the symbolic image database. Spatial reasoning techniques have been applied to pictorial database, in particular those using 2D strings as an index representation have been successful. In this thesis, we extend the existing three levels of type-i similarity to more levels to aid similarity retrieval more precisely. There are 13 spatial operators which were introduced by Lee and Hsu to completely represent spatial relationships in 1D space. But, they just combined the 13 spatial relationships on x- and y-axis to represent the spatial relationships in 2D space by 13 times 13 = 169 spatial relationships. However, the 169 spatial relationships are still not sufficient to show all kinds of spatial relationships between any two objects in 2D space. For example, the directional relationships, like North or South West, exist in 2D space and is difficult to be deducted from those 13 spatial operators. Thus, we add the nine directional relationships to the 169 spatial relationships in 2D space. In this way, we can distinguish up to 289 spatial relationships in 2D space. Moreover, in our proposed strategy, we also take care of the problem caused by the MBRs. In most of the previous approaches for iconic indexing, for simplifying the concerns, they apply the MBRs of two objects to define the spatial relationship between them. The topological relationships, however, between objects can be quite different from the spatial relationship of their respective $MBR$s. Therefore, sometimes, it is hard to correctly describe the spatial relationship of the objects in terms of the relationships between their corresponding MBRs. To improve this drawback resulted from MBRs, we adopting the concept of topological relationships in our proposed strategy. Good access methods for large image databases are important for efficient retrieval. The signature files can be viewed as a preselection searching filter to prune off the unsatisfied images. In order to solve the ambiguity of the MBRs and to present the spatial relationships in two dimensional space completely, we propose a hybrid approach-based signature extraction method for similarity retrieval. From our simulation study, we show that our approach can provide a higher rate of a correct match and requires a smaller storage cost than Lee et al.'s 2D B-based signature approach. In some case, the correct match rate based on our proposed strategy can be up to 42.18%, while it is just 16.66% in Lee et al.'s strategy. Moreover, the worst case of the storage cost required in our proposed strategy is 1686 bits. But, it always needs 2015 bits in Lee et al.'s strategy.

Abstract Modern technology has made it possible to produce, process, transmit and store digital images efficiently. Consequently, the amount of visual information is increasing at an accelerating rate in many diverse application areas. To fully exploit this new content-based image retrieval techniques are required. Document image retrieval systems can be utilized in many organizations which are using document image databases extensively. This thesis presents document image retrieval techniques and new approaches to improve database content. The goal of the thesis is to develop a functional retrieval system and to demonstrate that better retrieval results can be achieved with the proposed database generation methods. Retrieval system architecture, a document data model, and tools for querying document image databases are introduced. The retrieval framework presented allows users to interactively define, construct and combine queries using document or image properties: physical (structural), semantic, textual and visual image content. A technique for combining primitive features like color, shape and texture into composite features is presented. A novel search base reduction technique which uses structural and content properties of documents is proposed for speeding up the query process. A new model for database generation within the image retrieval system is presented. An approach for automated document image defect detection and management is presented to build high quality and retrievable database objects. In image database population, image feature profiles and their attributes are manipulated automatically to better match with query requirements determined by the available query methods, the application environment and the user. Experiments were performed with multiple image databases containing over one thousand images. They comprised a range of document and scene images from different categories, properties and condition. The results show that better recall and accuracy for retrieval is achieved with the proposed optimization techniques. The search base reduction technique results in a considerable speed-up in overall query processing. The constructed document image retrieval system performs well in different retrieval scenarios and provides a consistent basis for algorithm development. The proposed modular system structure and interfaces facilitate its usage in a wide variety of document image retrieval applications.

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As advances of information technology, engineering consulting firms have gradually digitalized their documents and line-drawing images. Such digital libraries greatly facilitate document retrievals. However, engineers still face a challenging issue: searches and retrievals of line-drawing images in a digital library. With a small number of line-drawing images in a digital library, engineers can browse thumbnails for locating relevant images. As the number of line-drawing images increases, the manual browsing process is time-consuming and frustrated. In response to the need and importance of supporting efficient and effective retrieval of line-drawing images, this thesis aims to develop a line-drawing image retrieval system. Typically, a line-drawing image within an engineering document is associated with surrounding text for description or illustration purpose. Such surrounding text provides important information for automatically indexing the line-drawing image. With extracted indexes (or keywords), retrieval of line-drawing images can be accomplished using a traditional information retrieval technique. Specifically, in this study, we propose a line-drawing image retrieval system based on surrounding text. We develop four models for defining surrounding text boundaries for line-drawing images. Furthermore, two information retrieval techniques (one with and one without query expansion) are implemented and evaluated. According to our empirical evaluations, the surrounding text boundary model with image caption together with three sentences (preceding, image anchoring, and successive sentences) would result in the best retrieval effectiveness, as measured by recall and precision rates.

科学研究費補助金 研究種目:一般研究(C) 課題番号:026600124 研究代表者:巽 二郎 研究期間:1990-1991年度

Recent image quality assessment (IQA) metrics achieve high correlation with human perception of image quality. Naturally, it is of interest to produce even better results. One promising method is to weight image quality measurements by visual importance. To this end, we describe three strategies - visual fixation-based weighting, quality-based weighting and weighting based on distribution of local quality scores about the mean. By contrast with some prior studies we find that these strategies can improve the correlations with subjective judgment significantly. We demonstrate improvements on the SSIM index in both its multi-scale and single-scale versions, using the LIVE database as a test-bed. / text

There is an accelerating demand to access and work over the visual content of documents. Because of the insufficiency of text-based techniques for storing this data, content-based image retrieval (CBIR) systems have become a promising field. Due this fact, in this study a CBIR system is implemented that is Mpeg-7 compliant and ORDBMS based. The database contains images and their content summaries that are parsed from XML files. The summaries describe their dominant colors, color histograms, color spaces and labels, in order to be compliant with Mpeg-7. The query process requires only the summary not the image itself. Software implementation of the system is based on JSP and servlet technologies using Oracle database and Tomcat web server. It is shown that the usage of these tools in the proposed architecture brings security, portability, and speed.