• Journal of the Korean Data and Information Science Society
• /
• v.20 no.4
• /
• pp.639-647
• /
• 2009

From development of computer science, genetic algorithm has been applied to many fields for search like non-linear problem based on various variables and optimization process. Among others, in the data mining field, there are methods to select the best input variables for model accuracy and various predict models which were merged by using the genetic algorithm. In the meantime, to improve and preserve quality of the Hanwoo (Korean cattle) which is represented the agricultural industry in our country, we need to find out outstanding economical traits of Hanwoo in having specific genotype of single nucleotide polymorphism (SNP) which is inherited to next generation. According to, This research proposed the selecting method to find genotype of SNPs marker which affects economical traits of the Hanwoo by using the genetic algorithm. And we selected the best genotypes of the principal SNPs marker by applying to real data on Hanwoo genetic.

• Journal of Broadcast Engineering
• /
• v.23 no.5
• /
• pp.628-635
• /
• 2018

In this paper, we propose a fast motion estimation algorithm which is important in video encoding. So many fast motion estimation algorithms have been published for improving prediction quality and computational reduction. In the paper, we propose an algorithm that reduces unnecessary computation, while almost keeping prediction quality compared with the full search algorithm. The proposed algorithm calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, and finds optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain fast computational speed by reducing unnecessary computations. Additionally, the proposed algorithm can be used with conventional fast motion estimation algorithms and prove it in the experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.7
• /
• pp.910-916
• /
• 2021

In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.55-66
• /
• 2024

Gender classification techniques have received a lot of attention from researchers because they can be used in various fields such as forensics, surveillance systems, and demographic studies. As previous studies have shown that there are distinctive features between male and female gait, various techniques have been proposed to classify gender from three dimensional(3-D) gait data. However, some of the gait features extracted from 3-D gait data using existing techniques are similar or redundant to each other or do not help in gender classification. In this study, we propose a method to select features that are useful for gender classification using a correlation-based feature selection technique. To demonstrate the effectiveness of the proposed feature selection technique, we compare the performance of gender classification models before and after applying the proposed feature selection technique using a 3-D gait dataset available on the Internet. Eight machine learning algorithms applicable to binary classification problems were utilized in the experiments. The experimental results show that the proposed feature selection technique can reduce the number of features by 22, from 82 to 60, while maintaining the gender classification performance.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2002.11a
• /
• pp.303-307
• /
• 2002

효율적인 웹 마이닝을 위해서는 방대한 인터넷 공간에서 사용자가 원하는 정보를 찾아내고, 이들 중 보다 유용하다고 판단되어진 자료를 선별적으로 제시할 수 있어야 한다. 본 논문에서는 웹 컨텐츠 분석과 HTML 문서들 사이의 링크 연결의 패턴 분석을 기반으로 하는 웹 구조 분석 방법들을 검토하고, 웹 검색 시스템을 구현하여 결과를 분석하였다. 이를 위해 웹 문서의 내용을 인덱싱한 뒤 질의와의 관련성의 확률을 구하는 랭귀지 검색 모델에 링크 구조 분석을 이용한 순위 알고리즘을 사용하여 좋은 결과를 얻고자 하였다. 또한 기존의 링크 관련 알고리즘에서 알려진 문제점을 해결하기 위한 몇가지 테크닉을 사용하였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2004.10a
• /
• pp.211-213
• /
• 2004

오늘날 인터넷은 의식주와 더불어 삶에 유용한 다양한 정보를 제공하늘 생활 필수품이다. 의식주가 인간의 육체적인 건강을 담당한다면, 인터넷은 정신적인 삶의 질을 담당한다. 그런데 음란사이트는 아직 정신적으로 미숙한 청소년들에게 선별 없이 개방되고 쉽게 노출될 수 있다. 이 논문에서는 웹사이트의 문서가 음란 문서인지 비음란 문서인지를 바르게 판정하기 위하여 유전 알고리즘을 이용하여 단어에 가중치를 배정하는 문제에 대하여 연구한다. 실험 결과 이렇게 배정된 가중치를 이용하여 평균 93.84%의 인식률로 음란 문서와 비음란 문서를 식별할 수 있었다. 여기서 문서의 음란여부를 판정하기 위하여 가중치를 배정하는 단어는 Zipf's law에 기반 하여 선정하였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10a
• /
• pp.175-177
• /
• 2001

기존의 문서 클러스터링 알고리즘은 모든 문서가 각각 하나의 클러스터에만 할당되도록 설계되어 문서에 여러 개의 주제가 포함되어 있을지라도 문서는 유사도 비교에 의해 오직 하나의 플러스터에 포함된다는 단점이 있다. 본 연구에서는 이러한 문서 플러스터링 방법의 한계를 파악하기 위해 문서가 여러 개의 클러스터에 포함될 수 있는 계층적 중복 문서 클러스터링을 제안한다. 또한, 문서 클러스터링의 정확도를 높이기 위해서 불용어 제거 알고리즘을 이용해 불용어를 제거하여 클러스터링에 사용되는 키워드를 선별하고, 단어가중치 산출을 위한 TF*NHDF 공식을 제안한다.

• Journal of KIISE
• /
• v.43 no.8
• /
• pp.848-856
• /
• 2016

Seeking and recognizing maritime targets are very important tasks for maritime safety. While searching for maritime targets using radar is possible, recognition is conducted without automatic identification system, radio communicator or visibility. If this recognition is not feasible, radar operator must tediously recognize maritime targets using movement features on radar base on know-how and experience. In this paper, to support the radar operator's mission of continuous observation, we propose an algorithm for automatic recognition of an unknown ship using movement features on radar and a method of detecting potential ship related accidents. We extract features from contact range, course and speed of four types of vessels and evaluate the recognition accuracy using SVM and suggest a method of detecting potential ship related accidents through the algorithm. Experimentally, the resulting recognition accuracy is found to be more than 90% and presents the possibility of detecting potential ship related accidents through the algorithm using information of MV Sewol. This method is an effective way to support operator's know-how and experience in various circumstances and assist in detecting potential ship related accidents.

• Journal of Broadcast Engineering
• /
• v.22 no.1
• /
• pp.51-61
• /
• 2017

This paper proposes a method to generate panoramic images by combining conventional feature extraction algorithms (e.g., SIFT, SURF, MPEG-7 CDVS) with sensed data from an inertia sensor to enhance the stitching results. The challenge of image stitching increases when the images are taken from two different mobile phones with no posture calibration. Using inertia sensor data obtained by the mobile phone, images with different yaw angles, pitch angles, roll angles are preprocessed and adjusted before performing stitching process. Performance of stitching (e.g., feature extraction time, inlier point numbers, stitching accuracy) between conventional feature extraction algorithms is reported along with the stitching performance with/without using the inertia sensor data.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.2
• /
• pp.193-198
• /
• 2022

Recently, place that you need to check wearing mask and body temperature to prevent the proliferation of COVID-19 increased. But these things often measured by man manually or by machine one by one, result may be different by measuring ways, so it wastes workforce. Also, the machine generally just measures the highest temperature of the face, criteria for fever can't be trusted too. A bottleneck may occur due to crowding of people at the entrance, and because most of the measurement sites are at one entrance, it is inconvenient to track the movement of COVID-19 Confirmed cases. Thus, in this study, we intend to propose a method for suppressing the spread of infection by automatically classifying and displaying in real time using camera, thermal camera, Haar Cascade, and result selection algorithm.