Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
The KIPS Transactions:PartB
Journal Basic Information
Journal DOI :
Korea Information Processing Society
Editor in Chief :
Volume & Issues
Volume 19B, Issue 4 - Aug 2012
Volume 19B, Issue 3 - Jun 2012
Volume 19B, Issue 2 - Apr 2012
Volume 19B, Issue 1 - Feb 2012
Selecting the target year
Detection of Pavement Region with Structural Patterns through Adaptive Multi-Seed Region Growing
Weon, Sun-Hee ; Joo, Sung-Il ; Na, Hyeon-Suk ; Choi, Hyung-Il ;
The KIPS Transactions:PartB, volume 19B, issue 4, 2012, Pages 209~220
DOI : 10.3745/KIPSTB.2012.19B.4.209
In this paper, we propose an adaptive pavement region detection method that is robust to changes of structural patterns in a natural scene. In order to segment out a pavement reliably, we propose two step approaches. We first detect the borderline of a pavement and separate out the candidate region of a pavement using VRays. The VRays are straight lines starting from a vanishing point. They split out the candidate region that includes the pavement in a radial shape. Once the candidate region is found, we next employ the adaptive multi-seed region growing(A-MSRG) method within the candidate region. The A-MSRG method segments out the pavement region very accurately by growing seed regions. The number of seed regions are to be determined adaptively depending on the encountered situation. We prove the effectiveness of our approach by comparing its performance against the performances of seed region growing(SRG) approach and multi-seed region growing(MSRG) approach in terms of the false detection rate.
Experimental Analysis of Algorithms of Splitting and Connecting Snake for Extracting of the Boundary of Multiple Objects
Cui, Guo ; Hwang, Jae-Yong ; Jang, Jong-Whan ;
The KIPS Transactions:PartB, volume 19B, issue 4, 2012, Pages 221~224
DOI : 10.3745/KIPSTB.2012.19B.4.221
The most famous algorithm of splitting and connecting Snake for extracting the boundary of multiple objects is the nearest method using the distance between snake points. It often can`t split and connect Snake due to object topology. In this paper, its problem was discussed experimentally. The new algorithm using vector between Snake segment is proposed in order to split and connect Snake with complicated topology of objects. It is shown by experiment of two test images with 3 and 5 objects that the proposed one works better than the nearest one.
A Research on Object Detection Technology for the Visually Impaired
Jeong, Yeon-Kyu ; Kim, Byung-Gyu ; Lee, Jeong-Bae ;
The KIPS Transactions:PartB, volume 19B, issue 4, 2012, Pages 225~230
DOI : 10.3745/KIPSTB.2012.19B.4.225
In this paper, a blind person using a white cane as an adjunct of the things available sensing technology has been implemented. Sensing technology to implement things ultrasonic sensors and a webcam was used to process the data from the server computer. Ultrasonic sensors detect objects within 4meter people distinguish between those things that if the results based on the results will sound off. In this study, ultrasonic sensors, object recognition and human perception with the introduction of techniques and technologies developed for detecting objects in the lives of the visually impaired is expected to be greater usability.
Regulatory Focus Classification for Web Shopping Consumers According to Product Type
Baik, Jong-Bum ; Han, Chung-Seok ; Jang, Eun-Young ; Kim, Yong-Bum ; Choi, Ja-Young ; Lee, Soo-Won ;
The KIPS Transactions:PartB, volume 19B, issue 4, 2012, Pages 231~236
DOI : 10.3745/KIPSTB.2012.19B.4.231
According to consumer behavior theory, human propensity can be divided into two regulatory focus types: promotion and prevention. These two types have much influence on the consumer`s decision in many diverse areas. In this research, we apply regulatory focus theory to personalized recommendation to minimize the cold start problem and to improve the performance of recommendation algorithms. To achieve this goal, we extract the consumer behavior variables and information exploration activity index from web shopping logs. We then use them for classifying regulatory focus of the consumer. This research has the contribution to show the possibility of systematization of consumer behavior theory as an interdisciplinary research tool of social science and information technology. Based on this attempt, we will extend the research to IT services adapting theories on other areas.
A Document Classification System Using Modified ECCD and Category Weight for each Document
Han, Chung-Seok ; Park, Sang-Yong ; Lee, Soo-Won ;
The KIPS Transactions:PartB, volume 19B, issue 4, 2012, Pages 237~242
DOI : 10.3745/KIPSTB.2012.19B.4.237
Web information service needs a document classification system for efficient management and conveniently searches. Existing document classification systems have a problem of low accuracy in classification, if a few number of feature words is selected in documents or if the number of documents that belong to a specific category is excessively large. To solve this problem, we propose a document classification system using `Modified ECCD` feature selection method and `Category Weight for each Document`. Experimental results show that the `Modified ECCD` feature selection method has higher accuracy in classification than
and the ECCD method. Moreover, combining the `Category Weight for each Document` feature value and `Modified ECCD` feature selection method results better accuracy in classification.
Improving the Performance of Document Similarity by using GPU Parallelism
Park, Il-Nam ; Bae, Byung-Gurl ; Im, Eun-Jin ; Kang, Seung-Shik ;
The KIPS Transactions:PartB, volume 19B, issue 4, 2012, Pages 243~248
DOI : 10.3745/KIPSTB.2012.19B.4.243
In the information retrieval systems like vector model implementation and document clustering, document similarity calculation takes a great part on the overall performance of the system. In this paper, GPU parallelism has been explored to enhance the processing speed of document similarity calculation in a CUDA framework. The proposed method increased the similarity calculation speed almost 15 times better compared to the typical CPU-based framework. It is 5.2 and 3.4 times better than the methods by using CUBLAS and Thrust, respectively.