• Journal of Digital Convergence
• /
• v.15 no.4
• /
• pp.267-273
• /
• 2017

With the development of various devices and communication technologies, the production and distribution of various multimedia contents are increasing exponentially. In order to retrieve multimedia data such as images and videos, an approach different from conventional text-based retrieval is needed. Color and shape are key features used in content-based image retrieval, which quantifies and analyzes various physical features of images and compares them to search for similar images. Color and shape have been used as independent features, but the two features are closely related in terms of cognition. In this paper, a method of describing the spatial distribution of color using a complex color model that projects three-dimensional color information onto two-dimensional complex form is proposed. Experimental results show that the proposed method can efficiently represent the shape of spatial distribution of colors by frequency transforming the complex image and reconstructing it with only a few coefficients in the low frequency.

• International Journal of Computer Science & Network Security
• /
• v.23 no.9
• /
• pp.77-90
• /
• 2023

Today, crops face many characteristics/diseases. Insect damage is one of the main characteristics/diseases. Insecticides are not always effective because they can be toxic to some birds. It will also disrupt the natural food chain for animals. A common practice of plant scientists is to visually assess plant damage (leaves, stems) due to disease based on the percentage of disease. Plants suffer from various diseases at any stage of their development. For farmers and agricultural professionals, disease management is a critical issue that requires immediate attention. It requires urgent diagnosis and preventive measures to maintain quality and minimize losses. Many researchers have provided plant disease detection techniques to support rapid disease diagnosis. In this review paper, we mainly focus on artificial intelligence (AI) technology, image processing technology (IP), deep learning technology (DL), vector machine (SVM) technology, the network Convergent neuronal (CNN) content Detailed description of the identification of different types of diseases in tomato and potato plants based on image retrieval technology (CBIR). It also includes the various types of diseases that typically exist in tomato and potato. Content-based Image Retrieval (CBIR) technologies should be used as a supplementary tool to enhance search accuracy by encouraging you to access collections of extra knowledge so that it can be useful. CBIR systems mainly use colour, form, and texture as core features, such that they work on the first level of the lowest level. This is the most sophisticated methods used to diagnose diseases of tomato plants.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.5
• /
• pp.1093-1102
• /
• 1996

For the reuse, configuration management, and version control of softwares, the composition of retrieval systems and library are most important matters, which makes it possible to retrieve the concerned software components. Retrieval systems, which is able to store many components, must make it possible to retrieve the concerned components with deadwoods in the fastest way. Based either on keyboards or the concept of inverted file on the part of content is usually used in the current retrieval systems. However, in this paper, new retrieval systems are suggested with using set and bag class with Smalltalk language, one of object- oriented programming language, based either on the keywords or on the part of content to find out the concerned components. This method is improved the function of user interface and its management, In this paper, library is also suggested along with the new retrieval systems, and user interface is designed and implemented for its management and control. The new retrial systems of this paper can be employed by interface in another language, and this system is to provide the concerned user with the appropriate retrieval systems and library for the version control.

• The KIPS Transactions:PartB
• /
• v.10B no.5
• /
• pp.543-552
• /
• 2003

An increasing in quantity of multimedia data brought a new problem that expected data should be retrieved fast and exactly. The adequate representation is a key element for the efficient retrieval. For this reason, MPEG-7 standard was established for description of multimedia data in 2001. However, the content of the standard is massive and the approach method is not clear for real application system yet, because of properties of MPEG-7 standard that has to include a lot of potential cases. In this paper, we suggested implementation scheme of retrieval system with using of only visual descriptors and presented the performance results of developed system. From the result of developed system, MPEG-7 VIRS (Video/Image Retrieval System), we analyzed the retrieval results between using individual descriptor and using multiple descriptors, and showed a layout for real application system.

• Journal of the Korean Institute of Telematics and Electronics T
• /
• v.36T no.1
• /
• pp.93-102
• /
• 1999

In this paper, we propose a data model and a retrieval method for content-based video query After partitioning a video into frame sets of same length which is called video-window, each video-window can be mapped to a point in a multidimensional space. A video can be represented a trajectory by connection of neighboring video-window in a multidimensional space. The similarity between two video-windows is defined as the euclidean distance of two points in multidimensional space, and the similarity between two video segments of arbitrary length is obtained by comparing corresponding trajectory. A new retrieval method with filtering and refinement step if developed, which return correct results and makes retrieval speed increase by 4.7 times approximately in comparison to a method without filtering and refinement step.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.11a
• /
• pp.612-615
• /
• 2006

The management of image information settles as an important field with the advent of multimedia age and we are in need of the effective retrieval method to manage systematically image information. It is used to color, texture, and shape features for content-based image retrieval. And existing methods using multiple features have problems that the retrieval process is embarrassed because each weight is set up manually. So we have solved these problems by assignment of weight applying fuzzy integral. This paper proposed the optimized values of fuzzy measure by experiments.

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.1
• /
• pp.1-7
• /
• 2002

In this paper, when users choose a query image, we implemented a content-based image retrieval system that users can simply choose and extract a object region of query wanted with not only a whole image but various objects in it. Histogram is obtained by improved HSV transformations from query image and then candidate images are retrieved rapidly by a 1st similarity measure with histogram intersection using representative colors of query image. And finally retrieved images are extracted since 2nd similarity measure with banded autocorrelogram is performed so that recall and precision are improved by combining two retrieval methods that can make up for respective weak points. Moreover images in the database are indexed automatically within feature library that makes possible to retrieve images rapidly.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.10B
• /
• pp.1902-1911
• /
• 1999

In this paper we present a content-based image retrieval algorithm using the visual feature vectors which describe the spatial characteristics of objects. The proposed technique uses the Gaussian mixture model(GMM) to represent multi-colored objects and the expectation maximization(EM) algorithm is employed to estimate the maximum likelihood(ML) parameters of the model. After image segmentation is performed based on GMM, the shape and color features are extracted from each object using Fourier descriptors and color histograms, respectively. Image retrieval consists of two steps: first, the shape-based query is carried out to find the candidate images whose objects have the similar shapes with the query image and second, the color-based query is followed. The experimental results show that the proposed algorithm is effective in image retrieving by using the spatial and visual features of segmented objects.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.453-456
• /
• 2003

Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.

• Proceedings of the IEEK Conference
• /
• 2000.11c
• /
• pp.129-132
• /
• 2000

In this paper, a multimedia database retrieval system is proposed using MPEG-7 meta data. Multimedia content based retrieval system is implemented with the MPEG-7 meta data extraction and matching technique. MPEG-7 descriptors and descriptor schemes are stored into the database with other meta data. When a query image is given, the descriptors and descriptor schemes of the query image are extracted and compared with the descriptors and descriptor schemes in the database. Finally, images having more similarity are retrieved.