• Title/Summary/Keyword: Image Queries

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GB-Index: An Indexing Method for High Dimensional Complex Similarity Queries with Relevance Feedback (GB-색인: 고차원 데이타의 복합 유사 질의 및 적합성 피드백을 위한 색인 기법)

  • Cha Guang-Ho
    • Journal of KIISE:Databases
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    • v.32 no.4
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    • pp.362-371
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    • 2005
  • Similarity indexing and searching are well known to be difficult in high-dimensional applications such as multimedia databases. Especially, they become more difficult when multiple features have to be indexed together. In this paper, we propose a novel indexing method called the GB-index that is designed to efficiently handle complex similarity queries as well as relevance feedback in high-dimensional image databases. In order to provide the flexibility in controlling multiple features and query objects, the GB-index treats each dimension independently The efficiency of the GB-index is realized by specialized bitmap indexing that represents all objects in a database as a set of bitmaps. Main contributions of the GB-index are three-fold: (1) It provides a novel way to index high-dimensional data; (2) It efficiently handles complex similarity queries; and (3) Disjunctive queries driven by relevance feedback are efficiently treated. Empirical results demonstrate that the GB-index achieves great speedups over the sequential scan and the VA-file.

Detection of Facial Direction for Automatic Image Arrangement (이미지 자동배치를 위한 얼굴 방향성 검출)

  • 동지연;박지숙;이환용
    • Journal of Information Technology Applications and Management
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    • v.10 no.4
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    • pp.135-147
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    • 2003
  • With the development of multimedia and optical technologies, application systems with facial features hare been increased the interests of researchers, recently. The previous research efforts in face processing mainly use the frontal images in order to recognize human face visually and to extract the facial expression. However, applications, such as image database systems which support queries based on the facial direction and image arrangement systems which place facial images automatically on digital albums, deal with the directional characteristics of a face. In this paper, we propose a method to detect facial directions by using facial features. In the proposed method, the facial trapezoid is defined by detecting points for eyes and a lower lip. Then, the facial direction formula, which calculates the right and left facial direction, is defined by the statistical data about the ratio of the right and left area in facial trapezoids. The proposed method can give an accurate estimate of horizontal rotation of a face within an error tolerance of $\pm1.31$ degree and takes an average execution time of 3.16 sec.

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Best Practice on Automatic Toon Image Creation from JSON File of Message Sequence Diagram via Natural Language based Requirement Specifications

  • Hyuntae Kim;Ji Hoon Kong;Hyun Seung Son;R. Young Chul Kim
    • International journal of advanced smart convergence
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    • v.13 no.1
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    • pp.99-107
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    • 2024
  • In AI image generation tools, most general users must use an effective prompt to craft queries or statements to elicit the desired response (image, result) from the AI model. But we are software engineers who focus on software processes. At the process's early stage, we use informal and formal requirement specifications. At this time, we adapt the natural language approach into requirement engineering and toon engineering. Most Generative AI tools do not produce the same image in the same query. The reason is that the same data asset is not used for the same query. To solve this problem, we intend to use informal requirement engineering and linguistics to create a toon. Therefore, we propose a sequence diagram and image generation mechanism by analyzing and applying key objects and attributes as an informal natural language requirement analysis. Identify morpheme and semantic roles by analyzing natural language through linguistic methods. Based on the analysis results, a sequence diagram and an image are generated through the diagram. We expect consistent image generation using the same image element asset through the proposed mechanism.

Content-based Image Retrieval System (내용기반 영상검색 시스템)

  • Yoo, Hun-Woo;Jang, Dong-Sik;Jung, She-Hwan;Park, Jin-Hyung;Song, Kwang-Seop
    • Journal of Korean Institute of Industrial Engineers
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    • v.26 no.4
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    • pp.363-375
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    • 2000
  • In this paper we propose a content-based image retrieval method that can search large image databases efficiently by color, texture, and shape content. Quantized RGB histograms and the dominant triple (hue, saturation, and value), which are extracted from quantized HSV joint histogram in the local image region, are used for representing global/local color information in the image. Entropy and maximum entry from co-occurrence matrices are used for texture information and edge angle histogram is used for representing shape information. Relevance feedback approach, which has coupled proposed features, is used for obtaining better retrieval accuracy. Simulation results illustrate the above method provides 77.5 percent precision rate without relevance feedback and increased precision rate using relevance feedback for overall queries. We also present a new indexing method that supports fast retrieval in large image databases. Tree structures constructed by k-means algorithm, along with the idea of triangle inequality, eliminate candidate images for similarity calculation between query image and each database image. We find that the proposed method reduces calculation up to average 92.9 percent of the images from direct comparison.

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Content-based Image Retrieval Using Fuzzy Multiple Attribute Relational Graph (퍼지 다중특성 관계 그래프를 이용한 내용기반 영상검색)

  • Jung, Sung-Hwan
    • The KIPS Transactions:PartB
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    • v.8B no.5
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    • pp.533-538
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    • 2001
  • In this paper, we extend FARGs single mode attribute to multiple attributes for real image application and present a new CBIR using FMARG(Fuzzy Multiple Attribute Relational Graph), which can handle queries involving multiple attributes, not only object label, but also color, texture and spatial relation. In the experiment using the synthetic image database of 1,024 images and the natural image database of 1.026 images built from NETRA database and Corel Draw, the proposed approach shows 6~30% recall increase in the synthetic image database and a good performance, at the displacements and the retrieved number of similar images in the natural image database, compared with the single attribute approach.

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A Physical Storage Design Method for Access Structures of Image Information Systems

  • Lee, Jung-A;Lee, Jong-Hak
    • Journal of Information Processing Systems
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    • v.14 no.5
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    • pp.1150-1166
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    • 2018
  • This paper presents a physical storage design method for image access structures using transformation techniques of multidimensional file organizations in image information systems. Physical storage design is the process of determining the access structures to provide optimal query processing performance for a given set of queries. So far, there has been no such attempt in the image information system. We first show that the number of pages to be accessed decreases as the shape of the given retrieval query region and that of the data page region become similar in the transformed domain space. Using these properties, we propose a method for finding an optimal image access structure by controlling the shapes of the page regions. For the performance evaluation, we have performed many experiments with a multidimensional file organization using transformation techniques. The results indicate that our proposed method is at least one to maximum five times faster than the conventional method according to the query pattern within the scope of the experiments. The result confirms that the proposed physical storage design method is useful in a practical way.

Clustering Representative Annotations for Image Browsing (이미지 브라우징 처리를 위한 전형적인 의미 주석 결합 방법)

  • Zhou, Tie-Hua;Wang, Ling;Lee, Yang-Koo;Ryu, Keun-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06c
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    • pp.62-65
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    • 2010
  • Image annotations allow users to access a large image database with textual queries. But since the surrounding text of Web images is generally noisy. an efficient image annotation and retrieval system is highly desired. which requires effective image search techniques. Data mining techniques can be adopted to de-noise and figure out salient terms or phrases from the search results. Clustering algorithms make it possible to represent visual features of images with finite symbols. Annotationbased image search engines can obtains thousands of images for a given query; but their results also consist of visually noise. In this paper. we present a new algorithm Double-Circles that allows a user to remove noise results and characterize more precise representative annotations. We demonstrate our approach on images collected from Flickr image search. Experiments conducted on real Web images show the effectiveness and efficiency of the proposed model.

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Web based Image Retrieval system using User Sketch and Example Image Queries (예제 이미지와 사용자 스케치 질의에 의한 웹 기반 이미지 검색 시스템)

  • Hwang Byung-Kon
    • Journal of Korea Society of Industrial Information Systems
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    • v.9 no.4
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    • pp.26-31
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    • 2004
  • Due to the recent explosive progress of Web, We can easily access a large number of images from m. In this paper, we describe our approach of developing a general purpose content based image retrieval system over the H using a Web agent. The Web agent extracts text information of images from the links and file contents in HTML. The proposed system retrieves the images from database using the query by sketch and the query by example on Web browser. Experimental results demonstrate the effectiveness of the new approach.

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Retrieval of video images based on Co-occurrence matrix (Co-occurrence matrix 기반 비데오 영상 검색)

  • 김규헌;정세윤;전병태;이재연;배영래
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.482-484
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    • 1998
  • Abstract : Multimedia data now one of the widely used information in all the fields as the fast developments of computer techniques have been made. Traditional database systems based on textual information have limitations when applied to multimedia information. This is because simple textual descriptions are ambiguous and inadequate for searching multimedia information for multimedia databases and digital libraries. Thus, especially for image data, which is one of the important multimedia information types, which can retrieve and browse image data on the basis of pictorial queries. Therefore, this paper presents an efficient method for describing texture information in image data.

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Multi-Thread Based Image Retrieval Agent in Distributed Environment (다중스레드를 이용한 분산 환경에서의 이미지 검색 에이전트)

  • Cha Sang-Hwan;Kim Soon-Cheol;Hwang Byung-Kon
    • Journal of Korea Multimedia Society
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    • v.8 no.3
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    • pp.355-361
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    • 2005
  • This paper proposed a system collecting image information by agents in multi-threaded environment and then retrieving them with content based image retrieval. This system uses multi threads to retrieve web information effectively, then improves efficiency of CPU cycles to reduce latency time, which is the time requesting queries, executing communication processing 4hat the retrieval agents perform and filtering the retrieval results. Also, the agents for image retrieval use Java language, which is platform independent, to be suitable for distributed environment. Using JDBC to save the retrieved images, the agents are connected to database. The images themselves are stored in distributed agents' databases, and only the image indexes are stored in an index server so that the efficiency of storage and retrieval time can be improved.

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