• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.894-897
• /
• 2000

In this paper, we present a content-based image retrieval method that is less sensitive to some rotations and translations of an image by using the fuzzy region segmentation. The algorithm retrieves similar images from a database using the two features of color and color spatial information. To index images, we use the average coordinates of color distribution to obtain the spatial information of each segmented region. Furthermore, we also propose the alternative to the ripple phenomenon, which is occurred in the conventional fuzzy region segmentation algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.2 s.308
• /
• pp.57-64
• /
• 2006

Tn this paper, We propose a user friendly object-based multimedia retrieval system using the HCNN(HippoCampus Neural Network. Most existing approaches to content-based retrieval rely on query by example or user based low-level features such as color, shape, texture. In this paper we perform a scene change detection and key frame extraction for the compressed video stream that is video compression standard such as MPEG. We propose a method for automatic color object extraction and ACE(Adaptive Circular filter and Edge) of content-based multimedia retrieval system. And we compose multimedia retrieval system after learned by the HCNN such extracted features. Proposed HCNN makes an adaptive real-time content-based multimedia retrieval system using excitatory teaming method that forwards important features to long-term memories and inhibitory learning method that forwards unimportant features to short-term memories controlled by impression.

• The KIPS Transactions:PartD
• /
• v.10D no.3
• /
• pp.547-558
• /
• 2003

From the viewpoint of that music melody has the similar features to time-series data, music melody is transformed to a time-series data with normalization and corrections and the similarity between melodies is defined as the Euclidean distance between the transformed time-series data. Then, based the similarity between melodies of a music object, melodies are clustered and the representative of each cluster is extracted as one of theme melodies for the music. To construct the theme melody index, a theme melody is represented as a point of the multidimensional metric space of M-tree. For retrieval of user's query melody, the query melody is also transformed into a time-series data by the same way of indexing phase. To retrieve the similar melodies to the query melody given by user from the theme melody index the range query search algorithm is used. By the implementation of the prototype system using the proposed theme melody index we show the effectiveness of the proposed methods.

• Journal of the Korean Society for information Management
• /
• v.18 no.3
• /
• pp.179-202
• /
• 2001

In information system research. there has been a strong interest in developing the user-centered interface. Interface metaphors have been regarded as a user friendly device of the information retrieval systems. This study is to discover overall opinions about metaphors and to evaluate the usability of metaphors used in the homepages and retrieval interfaces of academic and public libraries. It is found that some metaphors cause users to confuse because they are similar each others or don\`t have unique meaning and because some have weak relationship between texts and images of metaphors. It is necessary to develop a metaphor model suitable for the a specific interface. This study proposes to develop functional metaphors which can help users easily understand how to operate and remember the procedures, and which are based in user\`s knowledge and experiences. The organizational metaphors of a virtual community also will be considered as a new type of retrieval interfaces.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.4 s.42
• /
• pp.137-145
• /
• 2006

A user remembers a melody as not the combination of pitch and duration which is written in score but the contour which is composed of the relative pitch and duration. Because of the way of remembering a melody the previous Music Information Retrieval Systems which uses keyboard Playing or score as the main input melody are not easily acceptable in Query By Humming Systems. In this paper, we mention about the considerable checkpoints for Query By Humming System and previous researches. And we propose the feature extraction which is similar with the way of remembering a melody and similarity computation algorithms between melody in humming and melody in music. The proposed similarity computation algorithms solves the problem which can be happened when only uses the relative pitches by using relative durations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.1
• /
• pp.213-231
• /
• 2014

Existing image search systems allow users to search images by keywords, or by example images through content-based image retrieval (CBIR). On the other hand, users might learn more relevant textual information about an image from its text captions or surrounding contexts within documents or Web pages. Without such contexts, it's difficult to extract semantic description directly from the image content. In this paper, we propose an annotation watermarking system for users to embed text descriptions, and retrieve more relevant textual information from similar images. First, tags associated with an image are converted by two-dimensional code and embedded into the image by discrete wavelet transform (DWT). Next, for images without annotations, similar images can be obtained by CBIR techniques and embedded annotations can be extracted. Specifically, we use global features such as color ratios and dominant sub-image colors for preliminary filtering. Then, local features such as Scale-Invariant Feature Transform (SIFT) descriptors are extracted for similarity matching. This design can achieve good effectiveness with reasonable processing time in practical systems. Our experimental results showed good accuracy in retrieving similar images and extracting relevant tags from similar images.

• The Journal of the Korea Contents Association
• /
• v.17 no.11
• /
• pp.389-397
• /
• 2017

Recently semantic web document is produced and added in repository in a cloud computing environment and requires an intelligent semantic agent for analytical classification of documents and information retrieval. The traditional methods of information retrieval uses keyword for query and delivers a document list returned by the search. Users carry a heavy workload for examination of contents because a former method of the information retrieval don't provide a lot of semantic similarity information. To solve these problems, we suggest a key word frequency and concept matching based semantic clustering model using hadoop and NoSQL to improve classification accuracy of the similarity. Implementation of our suggested technique in a cloud computing environment offers the ability to classify and discover similar document with improved accuracy of the classification. This suggested model is expected to be use in the semantic web retrieval system construction that can make it more flexible in retrieving proper document.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.1
• /
• pp.28-33
• /
• 2003

This paper proposes a database index and retrieval method using the PCA(Principal Component Analysis). We perform a scene change detection and key frame extraction from the DC Image constructed by DCT DC coefficients in the compressed video stream that is video compression standard such as MPEG. In the extracted key frame, we use the PCA, then we can make codebook that has a statistical data as a codeword, which is saved as a database index. We also provide retrieval image that are similar to user's query image in a video database. As a result of experiments, we confirmed that the proposed method clearly showed superior performance in video retrieval and reduced computation time and memory space.

• The KIPS Transactions:PartB
• /
• v.11B no.6
• /
• pp.701-708
• /
• 2004

Existing contents-based video retrieval systems search by using a single method such as annotation-based or feature-based retrieval. Hence, it not only shows low search efficiency, but also requires many efforts to provide system administrator or annotator with a perfect automatic processing. Tn this paper, we propose an agent-based, and automatic and unified semantics-based video retrieval system, which support various semantics-retrieval of the massive video data by integrating the feature-based retrieval and the annotation-based retrieval. The indexing agent embodies the semantics about annotation of extracted key frames by analyzing a fundamental query of a user and by selecting a key-frame image that is ed by a query. Also, a key frame selected by user takes a query image of the feature-based retrieval and the indexing agent searches and displays the most similar key-frame images after comparing query images with key frames in the database by using the color-multiple-partition histogram techniques. Furthermore, it is shown that the performance of the proposed system can be significantly improved.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.1
• /
• pp.114-121
• /
• 2008

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system for Environment Education Contents which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted form query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.