• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.703-712
• /
• 2003

With the explosive growth n the numbers and sizes of imaging technologies, Content-Based Image Retrieval (CBIR) has been attacked the interests of researchers in the fields of digital libraries, image processing, and database systems. In general, in the case of query-by-image, in user has to select an image from database to query, even though it is not his completely desired one. However, since query-by-sketch approach draws a query shape according to the user´s desire it can provide more high-level searching interface to the user compared to the query-b-image. As a result, query-by-sketch has been widely used. In this paper, we propose a Java-based image retrieval system that consists of sketch query and image classification. We use two features such as color histogram and Haar wavelets coefficients to search similar images. Then the Leave-One-Out method is used to classify database images. The categories of classification are photo & painting, city & nature, and sub-classification of nature image. By using the sketch query and image classification, w can offer convenient image retrieval interface to user and we can also reduce the searching time.

• Economic and Environmental Geology
• /
• v.36 no.2
• /
• pp.133-139
• /
• 2003

The purpose of this study is the analyses of the relationship between geology and terrain/satellite image in the southern part of the Bandung, Indonesia to provide basic information fur geological survey. For this, topography, geology and satellite image were constructed to spatial database. Digital elevation, slope, aspect, curvature, hill shade of topography were calculated from the topographic database and lithology was imported from the geologi-cal database. Lineament, lineament density, and NDVI were extracted the Landsat TM satellite image. The results showed the close relationship between geology and terrain and satellited image. Each sedimentary rocks seldom correspond with geology and analyses of topography but as a whole fur sedimentary rocks coincide with them. Tuff and volcanic breccia in the volcanic rocks correspond with the result of terrain analyses. Talus deposit is well matched with the analyses of topography/satellite image.

• Proceedings of the IEEK Conference
• /
• 2000.06d
• /
• pp.11-14
• /
• 2000

We present an image retrieval method that improves retrieval rate by using the fusion of histogram and wavelet moment features. The key idea is that images similar to a query image are selected in DB by using the wavelet moment features. Then the result images are retrieved from the selected images by using histogram method. In order to evaluate the performance of the proposed method, we use Brodatz texture database, MPEG-7 T1 database and Corel Draw photo. Experimental result shows that the proposed method is better than each of histogram method and wavelet moment method.

• Proceeding of Spring/Autumn Annual Conference of KHA
• /
• 2000.11b
• /
• pp.173-178
• /
• 2000

As a way of decreasing trial and error that can occur in design, we investigated many kinds of material information and image information. We apprehended structures of material database and image database to suggest one of design method that provides information by connecting both databases. This has potentiality to improve the quality of design. Ultimately, this potentiality makes a great contribution towards strengthening competitiveness in design.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2000.11a
• /
• pp.120-121
• /
• 2000

신상품 개발을 위한 트랜드 이미지의 수집과 분석(타운워칭, 캐털로그 분석 등)은 이미 디자인 전개과정에 깊숙히 자리잡고 있는 기법이다. 그러나 대부분의 경우 트랜드 이미지의 수집은 디자이너의 직관에 의존하는 경우가 많았기 때문에 실질적인 시장상황을 반영한다고 하기에는 다소 힘들었던 것이 사실이다. (중략)

• Journal of IKEEE
• /
• v.22 no.4
• /
• pp.948-952
• /
• 2018

Haze removal is an object of scientific desire due to its various practical applications. Existing algorithms are founded upon histogram equalization, contrast maximization, or the growing trend of applying machine learning in image processing. Since machine learning-based algorithms solve problems based on the data, they usually perform better than those based on traditional image processing/computer vision techniques. However, to achieve such a high performance, one of the requisites is a large and reliable training database, which seems to be unattainable owing to the complexity of real hazy and haze-free images acquisition. As a result, researchers are currently using the synthetic database, obtained by introducing the synthetic haze drawn from the standard uniform distribution into the clear images. In this paper, we propose the enhanced equidistribution, improving upon our previous study on equidistribution, and use it to make a new database for training machine learning-based haze removal algorithms. A large number of experiments verify the effectiveness of our proposed methodology.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.2 no.3
• /
• pp.150-170
• /
• 2008

In recent years, main focus of research on image retrieval techniques is on content-based image retrieval. Text-based image retrieval schemes, on the other hand, provide semantic support and efficient retrieval of matching images. In this paper, based on Formal Concept Analysis (FCA), we propose a new image indexing and retrieval technique. The proposed scheme uses keywords and textual annotations and provides semantic support with fast retrieval of images. Retrieval efficiency in this scheme is independent of the number of images in the database and depends only on the number of attributes. This scheme provides dynamic support for addition of new images in the database and can be adopted to find images with any number of matching attributes.

• Journal of Computing Science and Engineering
• /
• v.8 no.2
• /
• pp.65-77
• /
• 2014

To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.1
• /
• pp.211-227
• /
• 2011

Content Based Image Retrieval (CBIR) is an approach for retrieving similar images from an image database based on automatically-derived image features. The quality of a retrieval system depends on the features used to describe image content. In this paper, we propose an image clustering system that takes a database of images as input and clusters them using k-means clustering algorithm taking into consideration color, texture and shape features. Experimental results show that the combination of the three features brings about higher values of accuracy and precision.

• Journal of Korea Multimedia Society
• /
• v.7 no.9
• /
• pp.1219-1232
• /
• 2004

Recently, the web sites, such as e-business sites and shopping mall sites, deal with lots of catalog image information and contents. As a result, it is required to support semantic-based image retrieval efficiently on such image data. This paper presents a semantic-based image retrieval system, which adopts XML and Fuzzy technology. To support semantic-based retrieval on product catalog images containing multiple objects, we use a multi-level metadata structure which represents the product information and semantics of image data. To enable semantic-based retrieval on such image data, we design a XML database for storing the proposed metadata and study how to apply fuzzy data. This paper proposes a system, generate the fuzzy data automatically to use the image metadata, that can support semantic-based image retrieval by utilizing the generating fuzzy data. Therefore, it will contribute in improving the retrieval correctness and the user's satisfaction on semantic-based e-catalog image retrieval.