• Journal of KIISE:Software and Applications
• /
• v.34 no.1
• /
• pp.1-10
• /
• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• The Korean Journal of Franchise Management
• /
• v.10 no.2
• /
• pp.33-47
• /
• 2019

Purpose - The purpose of this study is to classify and analyze existing studies from various angles through systematic literature review of how human resources development has been researched in the domestic franchise business. These studies are intended to suggest the direction in which human resource development research should be conducted in the future in the franchise business. Research design, data, and methodology - This study is based on systematic literature review methodology. It has gone through the process of subject language setting, literature search routing, search term selection, literature selection, literature classification and literature analysis. The systematic literature review identified 59 peer-reviewed dissertations and scientific journal publications on the subject of HRD in Korea franchise business. Result - This study analyzed by research methods, research industries, research population and dependent variable using the systematic review process. The literature studied in the 2000s mainly led to research on education and training of franchise employees in beauty franchise business. In the literature studied since 2010, human resources development was mainly studied in the supervisor in the restaurant franchise business, and in the study of competence rather than education and training. According to the research methods, statistical methods were mostly relatively simple, such as t-test or one-way distribution analysis until the 2000s, and after 2010, in-depth and structural studies using multiple return analysis, structural method analysis, path analysis, multi-dimensional scale analysis, AHP, etc were conducted. When classified by study dependant, early research until the 2000s focused on the study of education and training, which is an independent variable, on the satisfaction of education programs, job satisfaction, and immersion. On the other hand, studies conducted since 2010 have produced more complex results using various medium variants, and those related to management performance and relationship performance have been mainly studied, rather than the satisfaction of the education itself. Conclusions - While the domestic franchise business is expanding in terms of quantity, such as the number of franchises and franchises, the development in terms of quality for the joint growth of franchises and franchisees is still lacking. In order for the franchisee to continue to grow with each other, the franchisee must identify and develop their current performance or expected capabilities through capacity modeling at various targets and levels.

• Journal of KIISE:Databases
• /
• v.30 no.3
• /
• pp.320-335
• /
• 2003

Location-Based Services(LBS) give rise to location-based queries of which results depend on the locations of moving objects. One of important applications of LBS is to examine tracks of continuously moving objects. Moving objects databases need to provide 3-dimensional indexing for efficiently processing range queries on the movement of continuously changing positions. An extension of the 2-dimensional R-tree to include time dimension shows low space utilization and poor search performance, because of high overlap of index nodes and their dead space. To solve these problems, we propose a new R-tree based indexing technique, namely TR-tree. To increase storage utilization, we assign more entries to the past node by using the unbalanced splitting policy. If two nodes are highly overlapped, these nodes are forcibly merged. It is the forced merging policy that reduces the dead space and the overlap of nodes. Since big line segments can also affect the overlap of index nodes to be increased, big line segments should be clipped by the clipping policy when splitting overfull nodes. The TR-tree outperforms the 3DR-tree and TB-tree in all experiments. Particularly, the storage utilization of the TR-tree is higher than the R-tree and R*-tree.

• Archives of design research
• /
• v.16 no.1
• /
• pp.35-44
• /
• 2003

In the past era, acquisition and utilization of useful information was the main origin of competition. Nowadays, unlike that era, is the era of knowledge information(management) in which we should create a new knowledge on the basis of information and apply it to the field of practice. And more acquisition of information is no more the competitive power of any person, any company and any nation because in such the era of knowledge management, anyone can access and get the information he needs, utilizing internet-based searching system. Such demands of the times of knowledge management change rapidly in each field through knowledge management system and researches about knowledge management are actively processed in various academic branches. However, in our field of design, researches about those demands(knowledge management) still remain on the level of one-dimensional searching service for general data about design. Therefore, in this study, we developed building database of researches on form, color, aesthetical elements, preference image word, satisfaction etc. about CI/BI of home electronics goods, living goods, apparels, and food goods companies, also suggesting searching system through which you can obtain useful data and information helpful for designers to process CI/BI works of new product by using that database. Especially, in case of developing specific CI/BI, various search results through help of suggested system will supply a useful design concept. And more, cross table which is the result of analysis two-dimensional categorical data about existing design factors(such as form, color, aesthetical elements, preference image word, and satisfaction) will make contribution for designers to create a new design knowledge.

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.4
• /
• pp.237-243
• /
• 2007

In this paper, we propose the Real-time Dead-Pixel Detection and Compensation System for mobile camera and its hardware architecture. The CMOS image sensors as image input devices are becoming popular due to the demand for miniaturized, low-power and cost-effective imaging systems. However a conventional Dead-Pixel Detection Algorithm is disable to detect neighboring dead pixels and it degrades image quality by wrong detection and compensation. To detect dead pixels the proposed system is classifying dead pixels into Hot pixel and Cold pixel. Also, the proposed algorithm is processing line-detector and $5{\times}5$ window-detector consecutively. The line-detector and window-detector can search dead pixels by using one-dimensional(only horizontal) method in low frequency area and two-dimensional(vertical and diagonal) method in high frequency area, respectively. The experimental result shows that it can detect 99% of dead pixels. It was designed in Verilog hardware description language and total gate count is 23K using TSMC 0.25um ASIC library.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.9
• /
• pp.1754-1766
• /
• 2015

Packet classification carried out in Internet routers is one of the challenging tasks, because it has to be performed at wire-speed using five header fields at the same time. In this paper, we propose a leaf-pushed AQT bitmap trie. The proposed architecture applies the leaf-pushing to an area-based quad-trie (AQT) to reduce unnecessary off-chip memory accesses. The proposed architecture also applies a bitmap trie, which is a kind of multi-bit tries, to improve search performance and scalability. For performance evaluation, simulations are conducted by using rule sets ACL, FW, and IPC, with the sizes of 1k, 5k, and 10k. Simulation results show that the number of off-chip memory accesses is less than one regardless of set types or set sizes. Additionally, since the proposed architecture applies a bitmap trie, the required number of on-chip memory accesses is the 50% of the leaf-pushed AQT trie. In addition, our proposed architecture shows good scalability in the required on-chip memory size, where the scalability is identified by the stable change in the required memory sizes, as the size of rule sets increases.

• Journal of KIISE:Software and Applications
• /
• v.29 no.1_2
• /
• pp.80-90
• /
• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• Journal of Korea Multimedia Society
• /
• v.11 no.3
• /
• pp.315-322
• /
• 2008

Searching a location of the copied video in video database, signatures should be robust to video reediting, channel noise, time variation of frame rate. Several kinds of signatures has been proposed. Ordinal signature, one of them, is difficult to describe the spatial characteristics of frame due to the site of fixed window, $N{\times}N$, which is compute the average gray value. In this paper, I studied an algorithm of sequence matching in video copy detection for the copyright protection, employing the R-tree index method for retrieval and suggesting a robust ordinal signatures for the original video clips and the same signatures of the pirated video. Robust ordinal has a 2-dimensional vector structures that has a strong to the noise and the variation of the frame rate. Also, it express as MBR form in search space of R-tree. Moreover, I focus on building a video copy detection method into which content publishers register their valuable digital content. The video copy detection algorithms compares the web content to the registered content and notifies the content owners of illegal copies. Experimental results show the proposed method is improve the video matching rate and it has a characteristics of signature suitable to the large video databases.

• The KIPS Transactions:PartD
• /
• v.11D no.1
• /
• pp.11-22
• /
• 2004

As random access memory chip gets cheaper, it becomes affordable to realize main memory-based database systems. Consequently, reducing cache misses emerges as the most important issue in current main memory databases, in which CPU speeds have been increasing at 60% per year, compared to the memory speeds at 10% per you. In this paper, we design and implement a main-memory database system for real-time mobile GIS. Our system is composed of 5 modules： the interface manager provides the interface for PDA users； the memory data manager controls spatial and non-spatial data in main-memory using virtual memory techniques； the query manager processes spatial and non-spatial query : the index manager manages the MR-tree index for spatial data and the T-tree index for non-spatial index : the GIS server interface provides the interface with disk-based GIS. The MR-tree proposed propagates node splits upward only if one of the internal nodes on the insertion path has empty space. Thus, the internal nodes of the MR-tree are almost 100% full. Our experimental study shows that the two-dimensional MR-tree performs search up to 2.4 times faster than the ordinary R-tree. To use virtual memory techniques, the memory data manager uses page tables for spatial data, non- spatial data, T-tree and MR-tree. And, it uses indirect addressing techniques for fast reloading from disk.

• Journal of Korea Multimedia Society
• /
• v.8 no.10
• /
• pp.1369-1382
• /
• 2005

Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.