• Ocean Systems Engineering
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• v.11 no.4
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• pp.331-351
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• 2021

Underwater images are very much different from images taken on land, due to the presence of a higher disturbance ratio caused by the presence of water medium between the camera and the target object. These distortions and noises result in unclear details and reduced quality of the output image. An underwater image restoration method is proposed in this paper, which uses blurriness information, background light neutralization information, and red-light intensity to estimate depth. The transmission map is then estimated using the derived depth map, by considering separate attenuation coefficients for direct and backscattered signals. The estimated transmission map and estimated background light are then used to recover the scene radiance. Qualitative and quantitative analysis have been used to compare the performance of the proposed method against other state-of-the-art restoration methods. It has been shown that the proposed method can yield good quality restored underwater images. The proposed method has also been evaluated using different qualitative metrics, and results have shown that method is highly capable of restoring underwater images with different conditions. The results are significant and show the applicability of the proposed method for underwater image restoration work.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.67-72
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• 2023

In the past decade, Autonomous Vehicle Systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to be a crucial process in many applications, such as in autonomous driving, industrial automation and robotics. Especially in the case of autonomous vehicles, the efficient fusion of data from these two types of sensors is important to enabling the depth of objects as well as the classification of objects at short and long distances. This paper presents classification of objects using CNN based vision and Light Detection and Ranging (LIDAR) fusion in autonomous vehicles in the environment. This method is based on convolutional neural network (CNN) and image up sampling theory. By creating a point cloud of LIDAR data up sampling and converting into pixel-level depth information, depth information is connected with Red Green Blue data and fed into a deep CNN. The proposed method can obtain informative feature representation for object classification in autonomous vehicle environment using the integrated vision and LIDAR data. This method is adopted to guarantee both object classification accuracy and minimal loss. Experimental results show the effectiveness and efficiency of presented approach for objects classification.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.13-17
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• 2024

A color sensor is an optical sensor used to take pictures of objects, including the human body, and reproduce them on a monitor. A color sensor quantifies the red, green, and blue light coming from an object and expresses it as a digital number, and can judge the state of the object by comparing the values ​​or the ratio.In this study, the standard colors displayed on the monitor were measured using a color sensor, and the magnitudes of the red, green, and blue components, or RGB values, were compared with the values ​​indicated by the computer. When measured with the TCS 34725 color sensor, even when the light generated by the computer consists of only one or two of red, green, and blue light, the color sensor detected all three components. Additionally, when the colors of two monitors with the same RGB values ​​were measured using a color sensor, different RGB values ​​were measured. These results can be attributed to the imperfection of the color filters used to express colors on the monitor and the imperfect optical characteristics of the photodiodes used in the color sensor. When photographing an object and judging its condition based on its color, you must use the same type of camera or smartphone.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.1-15
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• 2011

The RLC systems is one of the intelligent transportation systems that has gained a nation-wide support for last decades and being installed to discourage motorists from running the red lights at signalized intersections. It is taken for granted that the RLC will provide motorists with increased safety, so that their installments are always justifiable. However, in order to acquire more efficiency and wider supports from the general public in future RLC installments, an improved methodology for analyzing the effects of the RLC systems is required. In order to satisfy this requirement, this research performed the following tasks. First, the number of signal violations after the RLC systems were investigated in order to check its resulting effects. Second, the number of crashes after the RLC systems were collected and compared with the number of signal violations. Third, a statistical analysis was carried out to develop the relationships between the signal violations and the crashes based on negative binomial distribution. The analysis revealed that the number of crashes has a close relationship with the RLC placement, traffic volume, vehicle speed, the number of phases, and the number of lanes for major approaches. Finally, based on the results found in this analysis, this research presents a methodology for analyzing the safety effects of placing the RLC that should be of service when investigating the economic consequences of the RLC systems.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.43-51
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• 2016

This paper presents the concept of "interactive teleprompter", which provides the user with interaction with oneself or other users for live television broadcasts or smart mirrors. In such interactive applications, eye contacts between the user and the regenerated image or between the user and other persons are important in handling psychological processes or non-verbal communications. Unfortunately, it is not straightforward to address the eye contact issues with conventional combination of normal display and video camera. To address this problem, we propose an "interactive" teleprompter enhanced from conventional teleprompter devices. Our interactive teleprompter can recognize the user's gestures by applying infra-red (IR) depth sensor. This paper also presents test results for a beam splitter which plays a critical role for teleprompter and is designed to handle both visual light for RGB camera and IR for Depth sensor effectively.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.642-655
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• 2018

Occupancy sensors installed in buildings and households turn off the light if the space is vacant. Currently PIR(pyroelectric infra-red) motion sensors have been utilized. Recently, the researches using camera sensors have been carried out in order to overcome the demerit of PIR that cannot detect stationary people. The detection of moving and stationary people is a main functionality of the occupancy sensors. In this paper, we propose an on-line human occupancy tracking method using convolutional neural network (CNN) and self-organizing map. It is well known that a large number of training samples are needed to train the model offline. To solve this problem, we use an untrained model and update the model by collecting training samples online directly from the test sequences. Using videos capurted from an overhead camera, experiments have validated that the proposed method effectively tracks human.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.3
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• pp.106-109
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• 2004

In-situ observational works had been done for the investigation of Cochlodinium polykrikoides cell distributions and abundances off the coast of Busan, Jinhae Bay, and Namhae to Tongyong area in the early June, 2004. The surface water of 11 was concentrated by passing through ${\Phi}$ 10 $\mu\textrm{m}$ mesh and cellular morphological characteristics of the species in the sample was observed under light microscope equipped with digital camera on the vessel. C. polykrikoides cells showed highest cell numbers ranging from 60 to 660 cells/1 at Jinhae Bay. Cell counts at offshore area of Busan ranged from 45 to 330 cells/1. However, no cell was found in the water between Namhae and Tongyong. C. polykrikoides found during the cruise had a large bright red and round cellular materials in one cell and two-celled chain of C. polykrikoides. The red material decreased as C. polykrikoides formed long chains through cell divisions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.727-731
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• 2005

We introduce a method of color-coded illumination that is simple and fast. The purpose of this study is the real-time shape measurement of three-dimensional object by using color-coded information. The object is illuminated by a prism color spectrum. A color spectrum of a white-light source is imaged onto the object by illumination from one certain direction. The object is observed by a color CCD camera from a direction of observation, which is different from the direction of illumination. It can be evaluated by the red, blue, green using a inherence colors of hue value are good point.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.29-42
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• 2016

Speeding is an important factor in traffic safety. Speed not only affects crash severity, but is also related to the possibility of crash occurrence. This study presents results from an analysis of 27,968 speed violation cases collected from 36 red light and speed enforcement cameras at signalized intersections in the city of Cheongju. Data included details of their violation history such as speeding tickets within a recent 3-year span and their demographic characteristics. The goal of this analysis is to understand the correlation between speed violations and various factors in terms of humans, vehicles and road environments. This study used descriptive statistics and Binary Logistics Regression(BLR) analysis with SPSS 20.0 software. The major results of this study are as follows. First, speed violations occurred at rural and suburban area. Second, about 25.6% of the violators committed to more than 20km/h over a speed limit. Third, the difference between speed violators and normal drivers clearly appeared in location of intersection(urban/rural/suburban area), gender and age. Finally, a statistically significant model(Hosmer and Lemeshow test: 11.586, p-value: 0.171) was developed through the BLR.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.41-47
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• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.