The notion of the image database is still unstructured. We examine recent work under this heading as well as related work in computer vision and conventional database technology. It appears that the principal difficul...
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The notion of the image database is still unstructured. We examine recent work under this heading as well as related work in computer vision and conventional database technology. It appears that the principal difficulties in fusing the two disciplines are: the arbitrary nature of discrete representations of continuous scenes; and the lack of linear ordering in two dimensions. A possible solution to these problems is suggested.
Spatial relationships between objects are important features for designing a content-based image retrieval system. In this paper, we propose a new scheme, called 9D-SPA representation, for encoding the spatial relatio...
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Spatial relationships between objects are important features for designing a content-based image retrieval system. In this paper, we propose a new scheme, called 9D-SPA representation, for encoding the spatial relations in an image. With this representation, important functions of intelligent image database systems such as visualization, browsing, spatial reasoning, iconic indexing, and similarity retrieval can be easily achieved. The capability of discriminating images based on 9D-SPA representation is much more powerful than any spatial representation method based on Minimum Bounding Rectangles or centroids of objects. The similarity measures using 9D-SPA representation provide a wide range of fuzzy matching capability in similarity retrieval to meet different user's requirements. Experimental results showed that our system is very effective in terms of recall and precision. In addition, the 9D-SPA representation can be incorporated into a two-level index structure to help reduce the search space of each query processing. The experimental results also demonstrated that, on average, only 0.1254 percent similar to 1.6829 percent of symbolic pictures ( depending on various degrees of similarity) were accessed per query in an image database containing 50,000 symbolic pictures.
Intending to contribute to constructing better multimedia network systems, we propose a new concept of image database system of which form of storage is featuring exponential or graceful oblivion and abrupt recollecti...
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Intending to contribute to constructing better multimedia network systems, we propose a new concept of image database system of which form of storage is featuring exponential or graceful oblivion and abrupt recollection like the human memory property. By virtue of this property of database storages that is realized by employing hierarchical or pyramidal image coding, the database memory and transmission costs can be significantly reduced. In this paper we will describe the details of the concept, the results of theoretical analysis based on a simplified model which reveals the effectiveness of the proposed system, the structure of an experimental prototype system and the result of an experimental image retrieval service carried out by implementing it over ATM high speed channels.
An image database of printed fabrics with repeating dot patterns was created to alleviate issues associated with management of and searches for numerous dot printed fabrics in the printing industry. The function of th...
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An image database of printed fabrics with repeating dot patterns was created to alleviate issues associated with management of and searches for numerous dot printed fabrics in the printing industry. The function of the database is to archive and allow retrieval of images. First, we discuss image archiving of repeating pattern-based dot printed fabrics. The color image was scanned by resolution of 200 dpi. The wavelet transformation was used to preprocess the image to obtain a scanned image 1/16 of the size of the original to be the stored image. To acquire images with repeating pattern color and repeating pattern template, the binary image of each pattern was obtained using the Sobel edge detection method and a morphological operation. Then pattern elements identical to the target pattern element were screened out. Afterwards, the centroid positions of these identical pattern elements were used to subdivide the repeating pattern color image and repeating pattern template image using a vertical vector method. Finally, the RGB 512-color histogram was used as the color feature of the dot printed fabrics, and the geometric and moment invariant feature values of the repeating pattern template image were used as the pattern feature of the dot printed fabrics. Our experimental results show that images can be acquired that are suitable for use in a dot printed fabric image database. The color and template images of the repeating patterns, which represent the image content of the printed fabrics, were obtained to create an image database of repeating pattern-based dot printed fabrics. This image database contains data on 300 printed fabrics which can be used for subsequent research on databaseimage retrieval.
Large image databases are commonly employed in applications like criminal records, customs, plant root databases, and voters' registration databases. Efficient and convenient mechanisms for database organization a...
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Large image databases are commonly employed in applications like criminal records, customs, plant root databases, and voters' registration databases. Efficient and convenient mechanisms for database organization and retrieval are essential. A quick and easy-to-use interface is needed which should also mesh naturally with the overall image management system. In this paper we describe the design and implementation of an integrated image database system. This system offers support for both alphanumeric query, based on alphanumeric data attached to the image file, and content-based query utilizing image examples. Content-based retrieval, specifically Query by image Example, is made possible by the SHOSLIF approach. Alphanumeric query is implemented by a collection of parsing and query modules. All these are accessible from within a user-friendly GUI.
In this paper the state of image database (IDB) systems which have been developed in the past few years is reviewed. We point out the essential problems in IDB design rather than classify the existing or proposed syst...
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In this paper the state of image database (IDB) systems which have been developed in the past few years is reviewed. We point out the essential problems in IDB design rather than classify the existing or proposed systems into an unestablished framework. After giving a general overview, the approaches to IDB and the elements of IDB systems are discussed. Finally, several representative IDB systems are presented.
Designing an automatic vehicle detection (AVD) system from still images or videos would be a useful tool to cater to the requirements of the traffic management system. Over the past few years, numerous databases have ...
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Designing an automatic vehicle detection (AVD) system from still images or videos would be a useful tool to cater to the requirements of the traffic management system. Over the past few years, numerous databases have been developed for the use of researchers in this field of AVD. However, most of them are not acceptable in the Indian scenarios due to certain practical constraints like the road infrastructure, nature of congestion, and vehicle types commonly found in India. The aim of this research is to develop a still image database, named as JUVDsi v1, which includes nine different types of vehicle classes collected through mobile phone cameras in various ways for designing an automated traffic management system. Identifying and analyzing the shortcomings of existing databases, the developed database presents an improvement to address such bottle-necks. Furthermore, the efficiency of this database is evaluated using an ensemble of three state-of-the-art deep learning architectures. At first, each vehicle in the scene images is localized and categorized. Five base object detection models, namely, YOLOv3, Faster-RCNN, RFCN, SSDv1 and SSDLitev2 are used. Finally, the Weighted Boxes Fusion technique is used as the ensemble method (ensemble of best three out of the five base learners), thereby enhancing the performance obtained by the individual object detection models. The database can be found at: https://***/JUVDsi/***.
Evaluation of an algorithm for finding a match for a random texture pattern in a large image database is presented. The algorithm was designed assuming that the random pattern may be subject to misregistration relativ...
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Evaluation of an algorithm for finding a match for a random texture pattern in a large image database is presented. The algorithm was designed assuming that the random pattern may be subject to misregistration relative to its representation in the database and assuming that it may have missing parts. The potential applications involve authentication of legal documents, bank notes, or credit cards, where thin fibers are embedded randomly into the document medium during medium fabrication. The algorithm achieves image matching by a three-step hierarchical procedure, which starts by matching parts of fiber patterns while solving the misregistration problem and ends up by matching complete fiber patterns. Performance of the algorithm is studied both theoretically and experimentally. Theoretical analysis includes the study of the probability that two documents have the same pattern, and the probability of the algorithm establishing a wrong match, as well as the algorithm's performance in terms of processing time. Experiments involving over 250,000 trials using databases of synthetic documents, containing up to 100,000 documents, were used to confirm theoretical predictions. In addition, experiments involving a database containing real images were conducted in order to confirm that the algorithm has potential in real applications.
A regularized color clustering algorithm is proposed to solve the color clustering problem in medical image database, By incorporating both measures of cluster separability and cluster compactness, regularized color c...
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A regularized color clustering algorithm is proposed to solve the color clustering problem in medical image database, By incorporating both measures of cluster separability and cluster compactness, regularized color clustering allows the automatic extraction of significant color groups with varying populations. Experimental results in different color spaces show that the regularized color clustering gives superior results in extracting significant distinct/abnormal color clusters without significant increases in cluster compactness. Furthermore, results of color clustering in different color spaces show that the LUV color space is more suitable for color clustering. Methods for selecting the regularization constants have also been suggested.
In this article, we present a new graphical navigation environment for image databases. Unlike "query by example" which focuses on similarities between images, the method we propose shows up visual differenc...
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ISBN:
(纸本)0819448184
In this article, we present a new graphical navigation environment for image databases. Unlike "query by example" which focuses on similarities between images, the method we propose shows up visual differences occurring along paths offered to the user. images are arranged to show an evolution along a direction, e.g. an axis that crosses the parameter space. This gives a global view of the database and allows the user to run all over the database in an organized way, and to focus on narrow areas by displaying sets of images.
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