• 한국군사과학기술학회지
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• 제12권4호
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• pp.524-531
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• 2009

In this paper, we propose an automatic image registration method for multi-sensor image fusion such as visible and infrared images. The registration is achieved by finding corresponding feature points in both input images. In general, the global statistical correlation is not guaranteed between multi-sensor images, which bring out difficulties on the image registration for multi-sensor images. To cope with this problem, mutual information is adopted to measure correspondence of features and to select faithful points. An update algorithm for projective transform is also proposed. Experimental results show that the proposed method provides robust and accurate registration results.

• 로봇학회논문지
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• 제4권4호
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• pp.298-304
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• 2009

This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.

• 인터넷정보학회논문지
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• 제11권1호
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• pp.129-141
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• 2010

본 논문에서는 사람의 행동 모니터링을 위한 멀티 센서 기반의 웨어러블 지능형 디바이스를 제안한다. 다중 행동을 인식하기 위해, 이미지 센서와 가속도 센서를 이용하여 행동 인식 알고리즘을 개발하였다. 멀티 센서로부터 얻은 데이터를 분석하기 위해 그리드 기반 옵티컬 플로우 방법을 제안하고 SVM 분류기법을 이용하였다. 이미지 센서로부터 얻은 모션 벡터의 방향과 크기를 이용하였고, 3축 가속도 센서로부터 얻은 데이터에서 FFT의 축과 크기와의 상관관계를 계산하였다. 실험 결과에서 이미지 센서 기반과 3축 가속도 센서기반의 행동 인식률은 각각 55.57 %, 89.97%를 보였으나 제안한 멀티센서기반의 행동인식률은 92.78% 를 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.169-172
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• 2002

A vision sensor measure range data using laser light source. This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which feeds foster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.584-587
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• 2002

A vision sensor measure range data using laser light source. This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which needs laster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• 한국측량학회지
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• 제29권5호
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• pp.449-457
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• 2011

As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.324-329
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• 2002

Generally, the laser vision sensor makes it possible design a highly reliable and precise range sensor at a low cost. When the laser vision sensor is applied to lap joint welding, however, there are many limitations. Therefore, a specially-designed hardware system has to be used. However, if the multi-lines are used instead of a single line, multi-range data can be generated from one image. Even under a set condition of 30fps, the generated 2D range data increases depending on the number of lines used. In this study, a laser vision sensor with a multi-line pattern is

• International Journal of Korean Welding Society
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• 제2권2호
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• pp.57-60
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• 2002

Generally, the laser vision sensor makes it possible design a highly reliable and precise range sensor at a low cost. When the laser vision sensor is applied to lap joint welding, however. there are many limitations. Therefore, a specially-designed hardware system has to be used. However, if the multi-lines are used instead of a single line, multi-range data .:an be generated from one image. Even under a set condition of 30fps, the generated 2D range data increases depending on the number of lines used. In this study, a laser vision sensor with a multi-line pattern is developed with conventional CCD camera to carry out high speed seam tracking in lap joint welding.

• 센서학회지
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• 제30권4호
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• pp.223-228
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• 2021

This work presents a low-power CMOS image sensor (CIS) with a multi-column-parallel (MCP) readout structure while focusing on improving its performance compared to previous works. A delta readout scheme that utilizes the image characteristics is optimized for the MCP readout structure. By simply alternating the MCP readout direction for each row selection, additional memory for the row-to-row delta readout is not required, resulting in a reduced area of occupation compared to the previous work. In addition, the bias current of a pre-amplifier in a successive approximate register (SAR) analog-to-digital converter (ADC) changes according to the operating period to improve the power efficiency. The prototype CIS chip was fabricated using a 0.18-㎛ CMOS process. A 160 × 120 pixel array with 4.4 ㎛ pitch was implemented with a 10-bit SAR ADC. The prototype CIS demonstrated a frame rate of 120 fps with a total power consumption of 1.92 mW.

• 한국군사과학기술학회지
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• 제13권3호
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• pp.445-452
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• 2010

Adequate segmentation of target objects from the background plays an important role for the performance of automatic target recognition(ATR) system. This paper presents a new segmentation algorithm using fuzzy thresholding to extract a target. The proposed algorithm consists of two steps. In the first step, the region of interest(ROI) including the target can be automatically selected by the proposed robust method based on the frame difference of each image sensor. In the second step, fuzzy thresholding with a proposed membership function is performed within the only ROI selected in the first step. The proposed membership function is based on the similarity of intensity and the adjacency of target area on each image. Experimental results applied to real CCD/IR images show a good performance and the proposed algorithm is expected to enhance the performance of ATR system using multi-sensors.