• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.12
• /
• pp.2905-2910
• /
• 2015

CW Radar Sensors can be categorized into Single and Dual by its IF output type. Dual IF type is used for detecting the direction of moving objects. However, Dual IF type has more complicated circuitry than Single IF type and higher cost due to more parts required. In this paper, we propose an algorithm for Single IF type CW radar sensors to detect the direction of moving objects. It performs FFT on signals created at IF output when an object moves and determines approach, stop and recede according to amplitude variations. In order to verify the algorithm, a function generator is used to create a virtual signal and confirmed that it accurately detects the directions according to amplitude variations.

• Journal of KIISE
• /
• v.44 no.7
• /
• pp.668-673
• /
• 2017

Deep neural networks have shown remarkable performance in various fields of pattern recognition such as voice recognition, image recognition and object detection. However, underlying mechanisms of the network have not been fully revealed. In this paper, we focused on empirical analysis of the network parameters. The Faster R-CNN(region-based convolutional neural network) was used as a baseline network of our work and three important parameters were analyzed: the dropout ratio which prevents the overfitting of the neural network, the size of the anchor boxes and the activation function. We also compared the performance of dropout and batch normalization. The network performed favorably when the dropout ratio was 0.3 and the size of the anchor box had not shown notable relation to the performance of the network. The result showed that batch normalization can't entirely substitute the dropout method. The used leaky ReLU(rectified linear unit) with a negative domain slope of 0.02 showed comparably good performance.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.40 no.1
• /
• pp.30-38
• /
• 2003

This paper presents an efficient region-based motion segmentation method for segmenting of moving objects in a traffic scene with a focus on a Video Monitoring System (VMS). The presented method consists of two phases: motion detection and motion segmentation. Using the adaptive thresholding technique, the differences between two consecutive frames are analyzed to detect the movements of objects in a scene. To segment the detected regions into meaningful objects which have the similar intensity and motion information, the regions are initially segmented using a k-means clustering algorithm and then, the neighboring regions with the similar motion information are merged. Since we deal with not the whole image, but the detected regions in the segmentation phase, the computational cost is reduced dramatically. Experimental results demonstrate robustness in the occlusions among multiple moving objects and the change in environmental conditions as well.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2011.01a
• /
• pp.257-260
• /
• 2011

본 논문에서는 비디오 데이터로부터 물체의 초기 움직임 영역을 자동으로 검출하는 방법을 소개한다. 제안하는 시스템은 먼저 입력 영상을 받아들인 후 인접된 영상으로부터 일정 크기의 정방향의 블록 단위로 움직임을 나타내는 모션 벡터를 추출한다. 그리고 추출된 모션벡터를 아웃라이어를 제거하는 강건 예측 알고리즘에 적용하여 배경에 해당하는 모션벡터와 잡음 및 움직이는 물체에 해당하는 모션벡터를 구분한다. 그런 다음, 군집화 알고리즘을 적용하여 이동하는 물체를 나타내는 모션벡터를 군집화하고, 군집화된 모션벡터에 해당하는 영역의 크기가 일정 수치 값 이상일 때 움직이는 물체가 감지되었다고 판단한다. 본 논문의 실험에서는 제안된 물체의 움직임 감지 방법이 기존의 방법에 비해 성능이 보다 우수함을 보인다.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.3
• /
• pp.97-107
• /
• 2017

In the field of automatic door, the infrared rays and microwave sensor are much used as the important components in charge of the motor's operation control of open and close through the incoming signal of object recognition. In case of existing system that the sensor of the infrared rays and microwave are applied to the automatic door, there are many malfunctions by the infrared rays and visible rays of the sun. Because the automatic doors are usually installed outside of building in state of exposure. The environmental change by temperature difference occurs the noise of object recognition detection signal. With this problem, the hardware fault that the detection sensor is unable to follow the object moving rapidly within detection area makes the sensing blind spot. This fault should be improved as soon as possible. Because It influences safety of passengers who use the automatic doors. This paper conducted an experiment to improve the detection area by installing extra ultrasonic sensor besides existing detection sensor. So, this paper realize the computing circuit and detection algorithm which can correctly and rapidly process the access route of objects moving fast and the location area of fixed obstacles by applying detection and advantages of ultrasonic signal to the automatic doors. With this, It is proved that the automatic door applying ultrasonic sensor is improved detection area of blind spot sensing through field test and improvement plan is proposed.

• Journal of Sensor Science and Technology
• /
• v.11 no.5
• /
• pp.255-262
• /
• 2002

Human retina is able to detect the edge of an object effectively. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge detection. There are several fluctuation factors which affect characteristics of MOSFETs during CMOS fabrication process and this effect appears as output offset of the vision chip which is composed of pixel arrays and readout circuits. The vision chip detecting edge information from input image is used for input stage of other systems. Therefore, the output offset of a vision chip determine the efficiency of the entire performance of a system. In order to eliminate the offset at the output stage, we designed a vision chip by using CDS(Correlated Double Sampling) technique. Using standard CMOS process, it is possible to integrate with other circuits. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Smart Media Journal
• /
• v.9 no.2
• /
• pp.9-15
• /
• 2020

In this paper, we propose a network model composed of Multi path Encoder-Decoder branches that can recognize each instance from the image. The network has two branches, Dot branch and Segmentation branch for finding the center point of each instance and for recognizing area of the instance, respectively. In the experiment, the CVPPP dataset was studied to distinguish leaves from each other, and the center point detection branch(Dot branch) found the center points of each leaf, and the object segmentation branch(Segmentation branch) finally predicted the pixel area of each leaf corresponding to each center point. In the existing segmentation methods, there were problems of finding various sizes and positions of anchor boxes (N > 1k) for checking objects. Also, there were difficulties of estimating the number of undefined instances per image. In the proposed network, an effective method finding instances based on their center points is proposed.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2002.05d
• /
• pp.622-625
• /
• 2002

부분방전의 특성을 연구하기 위하여 트리패턴을 추출하는 과정을 이용하는데, 트리열화 과정의 재현성이 떨어지고 트리의 패턴이 복잡함으로 기존의 시각적 관측으로는 트리성장의 정확한 정량화가 어렵기 때문에 영상처리에 의한 실시간 처리가 제안되고 있다. 본 연구에서는 부분방전의 측정을 위해 영상처리에 필요한 전반적인 과정을 제시하고, 특히 제안된 전경 물체 추출기법을 이용하여 측정된 영상에서 배경과 전경을 분할하여 전기트리를 측정하고자 한다. 전경 물체를 추출하기 위하여 전기트리를 측정한 영상에서 현재 프레임과 다음 프레임과의 차이 영상을 이용한 차이 검출 마스크를 사용하고, 추출된 전경 물체에서 에지를 검출하여 부분방전시 발생되는 전기트리를 실시간으로 계측 및 정량화하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.11a
• /
• pp.511-514
• /
• 2003

본 연구는 입력된 영상으로부터 특정한 형태를 이루고 있는 대상 물체를 추출함에 있어, 처리에 소요되는 시간 비용(Time cost)을 줄이는 것을 목적으로 하고 있다. 이를 위하여 특정 관심 지역(Region of Interest)이나 대상 물체(Tareet object)의 경계 검출(Boundary detection)을 하는 과정에 통계학적 수치자료(SSM : Statistical Shape Model)를 사용한 접근법을 이용하였다. 또한, 향후 연구 방향인 의료 영상해석(Medical image analysis)으로의 확장성을 고려, 의료 영상 해석에 많이 사용되어지는 MRI, CT, X-Ray 이미지가 Gray level 영상이라는 것을 감안하여 Gray level 영상을 연구 대상으로 삼았다.

• Proceedings of the Korean Information Science Society Conference
• /
• 1998.10c
• /
• pp.520-522
• /
• 1998

활성 윤곽선 모델(Active Contour Model : Snake)을 이용한 윤곽선 추출 방법에서는 물체를 검출하기 위해 잠재적 표면(potential surface) 위에서 지역 최소치를 향하여 다양한 힘을 가함으로써 물체의 윤곽선으로 활성 윤곽선 모델을 움직이게 한다. 활성 윤곽선 모델에서 영상의 관심있는 물체를 검출하기 위해서는 영상의 잠재적 표면 위에서 활성 윤곽선 모델이 지역 최소치를 향하여 활동적으로 움직이도록 다양한 힘을 효과적으로 제어해야 한다. 본 논문에서는 활성 윤곽선 모델이 적합한 지역 최소치를 향하여 적절하게 수렴하도록 활성 윤곽선 모델이 움직이는 잠재적 표면을 변형할 수 있는 영상 필터를 제안한다.