• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.1
• /
• pp.60-65
• /
• 2010

This paper describes the results of 2D mapping, feature detection and matching to create the surrounding environment in the mounted stereo camera on Mobile robot. Extract method of image's feature in real-time processing for quick operation uses the edge detection and Sum of Absolute Difference(SAD), stereo matching technique can be obtained through the correlation coefficient. To estimate the location of a mobile robot using ZigBee beacon and encoders mounted on the robot is estimated by Kalman filter. In addition, the merged gyro scope to measure compass is possible to generate map during mobile robot is moving. The Simultaneous Localization and Mapping (SLAM) of mobile robot technology with an intelligent robot can be applied efficiently in human life would be based.

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.6
• /
• pp.31-38
• /
• 2017

With the Development of Information Technology, Security is becoming very Important. Existing Security Systems are Mostly Expensive and Not Easy to Implement, and are Also very Complex when using Biometric Information. In this paper, We try to solve this Problem by Implementing a Low cost Internet based Security Terminal Using Fingerprint and Face Image. To Implement a Low-cost Security System, a Fingerprint Scanner and a Camera are installed in Raspberry pi, and the Scanned Image is encrypted with the AES-256 Algorithm and Transmitted to Cloud. Through This Study, We confirmed the Possibility of the Proposed System in view of Authentication, Cost Reduction, Security and Scalability.

• Annual Conference of KIPS
• /
• 2002.11a
• /
• pp.669-672
• /
• 2002

최근 멀티미디어 기술의 급속한 발달로 인해 개인의 신원 확인, 보안 시스템 등의 영역에서 얼굴과 관련된 연구가 활발히 진행 되고 있다. 기존의 연구에서는 원거리 추적이 어려우며, 연산시간, 잡음(noise), 배경과 조명등에 따라 추적 효율이 낮은 단점을 가지고 있다. 본 논문에서는 빠르고 정확한 얼굴 추적을 위한 차 영상 기법(differential image method)을 이용한 분할영역(segmentation region)에서 움직임(motion)과 피부색(skin color) 특성 기반의 객체분할추적(Tracking Of Object segmentation) 방법을 이용하였다. 객체분할추적은 얼굴을 하나의 객체(object)로 인식하고 제안한 방법으로 얼굴 부분만 분할하는 단계와 얼굴특징추출 단계를 적용하여 피부색 기반의 연구에서 나타난 입력영상(Current Frame)에서의 유동적인 피부색의 노출 대한 얼굴 추적 연구의 문제점을 해결했다. 시스템은 현재 컴퓨터에 일반적으로 사용되는 카메라를 이용하여 구현 하였고, 실시간(real-time) 영상에서 비교적 성공적인 얼굴 추적을 하였다[4].

• Annual Conference of KIPS
• /
• 2012.11a
• /
• pp.1162-1165
• /
• 2012

어미로부터 생후 21일령(또는 28일령)에 젖을 때는 어린 자돈들은 면역력이 약하여 통상 폐사율이 30~40%까지 치솟는 등 자돈 관리가 국내 양돈 농가의 가장 큰 문제 중 하나로 인식되고 있다. 본 논문에서는 이러한 양돈 농가의 문제를 해결하기 위하여 자돈사(새끼돼지 축사)에 카메라와 마이크를 설치하고 획득된 영상과 소리 정보를 이용하여 자돈들을 모니터링하는 시스템을 제안한다. 제안된 시스템은 실시간으로 유입되는 영상과 소리 스트림 데이터로부터 각각 움직임 벡터와 평균 피치 값을 추출하여 이미 설정된 정상 상황의 임계치 값을 넘는 순간부터를 불특정 이상 상황이라 판단한다. 실제, 경상남도 함양군의 한 돼지 농장에 A/V 센서 기반의 실험 환경을 구축하고 2012년 6월 한 달간의 이유자돈 돈사의 모니터링 데이터 셋을 취득하였고 전반기 15일간의 데이터 셋을 이용하여 자돈사 모니터링 시스템의 프로토타입을 설계 구현하였으며 후반기 15일간의 A/V 스트림 데이터로는 검증 실험을 수행하였다.

• Journal of IKEEE
• /
• v.25 no.1
• /
• pp.83-87
• /
• 2021

In harsh environments such as fog or fine dust, the cameras' detection ability for object recognition may significantly decrease. In order to accurately obtain important information even in bad weather, fog removal algorithms are necessarily required. Research has been conducted in various ways, such as computer vision/data-based fog removal technology. In those techniques, estimating the amount of fog through the input image's depth information is an important procedure. In this paper, a linear model is presented under the assumption that the image dark channel dictionary, saturation ∗ value, and sharpness characteristics are linearly related to depth information. The proposed method of haze removal through a linear model shows the superiority of algorithm performance in quantitative numerical evaluation.

• Smart Media Journal
• /
• v.11 no.9
• /
• pp.47-55
• /
• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.4
• /
• pp.50-58
• /
• 2017

Recently, some methods of converging heterogeneous fire sensor data have been proposed for effective fire detection, but the rule-based methods have low adaptability and accuracy, and the fuzzy inference methods suffer from detection speed and accuracy by lack of consideration for images. In addition, a few image-based deep learning methods were researched, but it was too difficult to rapidly recognize the fire event in absence of cameras or out of scope of a camera in practical situations. In this paper, we propose a novel fire detection system combining a deep learning algorithm based on CNN and fuzzy inference engine based on heterogeneous fire sensor data including temperature, humidity, gas, and smoke density. we show it is possible for the proposed system to rapidly detect fire by utilizing images and to decide fire in a reliable way by utilizing multi-sensor data. Also, we apply distributed computing architecture to fire detection algorithm in order to avoid concentration of computing power on a server and to enhance scalability as a result. Finally, we prove the performance of the system through two experiments by means of NIST's fire dynamics simulator in both cases of an explosively spreading fire and a gradually growing fire.

• Journal of Internet Computing and Services
• /
• v.18 no.4
• /
• pp.61-67
• /
• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.249-251
• /
• 2012

Augmented Reality (AR) enables the enhanced realism and interaction by providing the overlaid digital information on the user's view of the physical world. In this paper, we propose an AR-based ship design visualization system for presenting ship 3D model in smart phones or table PCs. The proposed system compute corner points and feature points by contour finding method and harris corner detector, and build a ship-design drawing database. By using SURF algorithm, key feature points are extracted from ship-design drawing image which is obtained by mobile camera. Then ship-design drawing image is recognized by matching the feature points stored in DB and extracted key feature points. 3D ship structures are visualized by overlaying the ship-design drawing image on the smart phone or table PC's screen. Compared to conventional 2D ship-design, proposed system helps to easily understand the structures of the ship and reduce the business design period. Thus, Enhanced competitiveness of business is expected.

• Journal of KIISE:Software and Applications
• /
• v.32 no.4
• /
• pp.258-267
• /
• 2005

We propose the ubiFloor system to track and recognize users in ubiquitous computing environments such as ubiHome. Conventional user identification systems require users to carry tag sensors or use camera-based sensors to be very susceptible to environmental noise. Though floor-type systems may relieve these problems, high cost of load cell and DAQ boards makes the systems expensive. We propose the transparent user identification system, ubiFloor, exploiting user's walking pattern to recognize the user with a set of simple ON/OFF switch sensors. The experimental results show that the proposed system can recognize the 10 enrolled users at the correct recognition rate of $90\%$ without users' awareness of the system.