• 전자공학회논문지
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• 제51권2호
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• pp.114-123
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• 2014

자동차용 영상 사고기록장치(블랙박스)는 도로위의 일반적인 상황만을 촬영하게 된다. 또한, 급격한 조도변화의 상황에서는 주위의 환경을 제대로 인식하기 어렵고 렌즈 자체의 왜곡이 매우 심하기 때문에 사고 발생 시 명확한 증거로 사용하기 어렵다. 이러한 문제를 해결하기 위한 첫 번째 방법으로 정규화된 밝기 정보의 수표현자인 NLD(Normalized Luminance Descriptor)값과 정규화된 명암정보의 수표현자인 NCD(Normalized Contrast Descriptor)값을 정의하여 추출하고 두 값의 관계를 갖는 영상의 수표현자인 NIQ(Normalized Image Quality)값을 사용하여 급격한 조도변화에 대응하였다. 두 번째로, 어안렌즈가 디자인되는 방법을 기본으로 하는 FOV(Field Of View)모델을 이용하여 렌즈의 왜곡을 보정한다. 결과적으로 두 가지 영상왜곡은 각각 감마보정 및 렌즈왜곡보정의 영상처리 기법을 사용하여 병렬로 처리한 후 이를 하나의 영상으로 통합하는 알고리즘을 제안한다.

• Journal of Biosystems Engineering
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• 제41권2호
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• pp.126-137
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• 2016

Purpose: The overall objective of this study was to evaluate the vegetation fraction of soybeans, grown under different cropping conditions using an unmanned aerial vehicle (UAV) equipped with a red, green, and blue (RGB) camera. Methods: Test plots were prepared based on different cropping treatments, i.e., soybean single-cropping, with and without herbicide application and soybean and barley-cover cropping, with and without herbicide application. The UAV flights were manually controlled using a remote flight controller on the ground, with 2.4 GHz radio frequency communication. For image pre-processing, the acquired images were pre-treated and georeferenced using a fisheye distortion removal function, and ground control points were collected using Google Maps. Tarpaulin panels of different colors were used to calibrate the multi-temporal images by converting the RGB digital number values into the RGB reflectance spectrum, utilizing a linear regression method. Excess Green (ExG) vegetation indices for each of the test plots were compared with the M-statistic method in order to quantitatively evaluate the greenness of soybean fields under different cropping systems. Results: The reflectance calibration methods used in the study showed high coefficients of determination, ranging from 0.8 to 0.9, indicating the feasibility of a linear regression fitting method for monitoring multi-temporal RGB images of soybean fields. As expected, the ExG vegetation indices changed according to different soybean growth stages, showing clear differences among the test plots with different cropping treatments in the early season of < 60 days after sowing (DAS). With the M-statistic method, the test plots under different treatments could be discriminated in the early seasons of <41 DAS, showing a value of M > 1. Conclusion: Therefore, multi-temporal images obtained with an UAV and a RGB camera could be applied for quantifying overall vegetation fractions and crop growth status, and this information could contribute to determine proper treatments for the vegetation fraction.

• Asian Journal of Atmospheric Environment
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• 제9권2호
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• pp.128-136
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• 2015

Sky View Factor (SVF) is one of the urban morfometri parameters that impact on the Urban Heat Island (UHI). SVF analisys was conducted in the city of Jakarta to investigate the relationship between urban temperature with urban morfometri. Jakarta City is the most populous city in the world that has a surrounding area $66,152km^2$ and the total population around 23 million people. The population of the city is the sixth highest in the world today. SVF measurements done by taking pictures at the six stations that have different morphological characteristics namely (1) the narrow streets Apartment Cempaka Mas (JS ITC), (2) the width of the road Apartment Cempaka Mas (JL ITC), (3) in front of Colleges Kanisius (DKK), (4) in front of office Journalist of Indonesia (DKWI), (5) Utan Kayu (UK), and (6) Tambun (TB). SVF value is obtained from the photgraphic image. Taking pictures at the location using a Nikon D90 camera with a Nikon Fisheye Nikkor 10.5 mm 1 : 2.8 G ED, further processed through a global mapper program. Therefore, the SVF derived from the six stations that vary 0.21 to 0.78. Temperature measurement is done during daylight hours from 06:00 am to 18:00 pm during the Western Part of Indonesia (WIB). Measurements performed at three different times, namely working days (HK) regular holidays (HCB) national holidays (HCN). The results showed that the highest average temperature of $33.32^{\circ}C$, occurring at UK station (SVF=0.45) at the time of HCB. Meanwhile, the average low temperature of $31.22^{\circ}C$ occurred at JLITC station (SVF=0.42). The two-time occurred on ordinary holidays. Maximum temperature of $38.4^{\circ}C$ occurred in Utan Kayu station (SFV=0.45) that occurred at 11.00 hrs, normal holidays. Furthermore minimum temperature 24.5 occurred at Tambun station (SVF=0.78) at 06.00 hrs in the morning at the usual holidays and national holidays. In general, the results showed that areas with large SVF has a lower temperature compared with areas with smaller SVF. Though, are not the only factors that matter, but this research may show that an increase in temperature in the city of Jakarta. Therefore, it is necessary to mitigate the serious from the government or society.