• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.114-123
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• 2014

Vehicle Black Box (Event Data Recorder EDR) only recognizes the general surrounding environments of load. In addition, general EDR is difficult to recognize the images of a sudden illumination change. It appears that the lens is being a severe distortion. Therefore, general EDR does not provide the clues of the circumstances of the accident. To solve this problem, we estimate the value of Normalized Luminance Descriptor(NLD) and Normalized Contrast Descriptor(NCD). Illumination change is corrected using Normalized Image Quality(NIQ). Second, we are corrected lens distortion using model of Field Of View(FOV) based on designed method of fisheye lens. As a result, we propose integration algorithm of two methods that correct distortions of images using each Gamma Correction and Lens Correction in parallel.

• Journal of Biosystems Engineering
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• v.41 no.2
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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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• v.9 no.2
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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.