Grid-Based Low Computation Image Processing Algorithm of Maritime Object Detection for Navigation Aids

Jeon, Ho-Seok; Park, Sung Hyun; Im, Tae-Ho

doi:10.3390/electronics12092002

Cited by 3 publications

(4 citation statements)

References 39 publications

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“…There are various image processing algorithms to divide sea and sky in ocean images; however, this paper does not discuss cropping algorithms, since they are out of its scope. This paper uses the work of Jeon 2023 [21] for the division achieves the most distinct results (results will be discussed in Section 4.2). Therefore, 100 is chosen for the threshold value in this paper.…”

Section: Cropping a Sky Regionmentioning

confidence: 99%

Section: Cropping a Sky Regionmentioning

confidence: 99%

“…There are various image processing algorithms to divide sea and sky in ocean images; however, this paper does not discuss cropping algorithms, since they are out of its scope. This paper uses the work of Jeon 2023 [21] for the division of sky and sea regions in an image. Figure 5 below provides an example of cropping only the sea area from the entire image.…”

Section: Cropping a Sky Regionmentioning

confidence: 99%

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RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

Hwang,

Park,

Park

et al. 2023

JMSE

Self Cite

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A number of accidents at sea are primarily caused by low visibility due to sea fog. Therefore, it is important to estimate sea fog intensity and visibility in real-time in the ocean environment. Visibility meters utilize optical sensors rather than visional information, so that the measured visibility data occasionally includes errors. Moreover, visibility meters have significant costs so that it is not viable to install them at various locations. Therefore, this paper proposes an algorithm called RDCP (Reduced Dark Channel Prior), which provides reliable estimation at a low cost by processing images captured from cameras, since they receive identical information as human eyes. For the estimation, the RDCP algorithm firstly acquires dark channels from an ocean image, then applies an optimized threshold value to the dark channels and crops out the sky region in the ocean image. For the estimation performance evaluation, 320 raw images captured from cameras at four different ports in Republic of Korea are used. Considering facilities in oceans, which are usually operated in power-limited environment, the processing time performance of PDCP is also examined. The experiments demonstrate that the RDCP algorithm provides reliable estimation performance in real-time.

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Section: Cropping a Sky Regionmentioning

confidence: 99%

Section: Cropping a Sky Regionmentioning

confidence: 99%

“…There are various image processing algorithms to divide sea and sky in ocean images; however, this paper does not discuss cropping algorithms, since they are out of its scope. This paper uses the work of Jeon 2023 [21] for the division of sky and sea regions in an image. Figure 5 below provides an example of cropping only the sea area from the entire image.…”

Section: Cropping a Sky Regionmentioning

confidence: 99%

See 1 more Smart Citation

RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

Hwang,

Park,

Park

et al. 2023

JMSE

Self Cite

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show abstract

“…When an object receives a sufficient amount of light in illumination, it will appear in its original color because it will reflect sufficiently [15]. In this respect, ambient lighting, the direction and amount of light are important issues in terms of image quality, accurate detection of objects and energy use [16,17]. In order to obtain successful results and save energy in image processing, a minimum ambient light level must be provided.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Lighting System Using Color-Based Image Processing for Object Detection in Robotic Handling Applications

Akış,

Dişlitaş

2024

Applied Sciences

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In applications reliant on image processing, the management of lighting holds significance for both precise object detection and efficient energy utilization. Conventionally, lighting control involves manual switching, timed activation or automated adjustment based on illuminance sensor readings. This research introduces an embedded system employing image processing methodologies for intelligent ambient lighting, focusing specifically on reference-color-based illumination for object detection and positioning within robotic handling scenarios. Evaluating the system’s efficacy entails analyzing the illuminance levels and power consumption through a tailored experimental setup. To minimize illuminance, the LED-based lighting system, controlled via pulse-width modulation (PWM), is calibrated using predetermined red, green, blue and yellow (RGBY) reference objects, obviating the need for external sensors. Experimental findings underscore the significance of color choice in detection accuracy, highlighting yellow as the optimal color requiring minimal illumination. Successful object detection based on color is demonstrated at an illuminance level of approximately 50 lx, accompanied by energy savings contingent upon ambient lighting conditions.

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RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

Hwang,

Park,

Kwon

et al. 2023

Preprint

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A number of accidents at sea are primarily caused by low visibility due to sea fog therefore, it is important to estimate sea fog intensity and visibility in real-time in the ocean environment. However, the existing estimation systems have significant costs so that it is not viable to install them at various locations, such as small vessels, minor ports, and a number of buoys. Therefore, this paper proposes an algorithm called RDCP (Reduced Dark Channel Prior) which provides the estimation at a low complexity and a low cost. For the estimation, the RDCP algorithm firstly acquires dark channels from an ocean image, then applies an optimized threshold value to the dark channels, and crops out the sky region in the ocean image. For the estimation performance evaluation, 320 raw images captured from cameras at four different ports in South Korea are used rather than artificially composed images. Considering facilities in oceans which are usually operated in the power limited environment, the processing time performance of PDCP are also examined. The experiments demonstrate that the RDCP algorithm provides reliable estimation performance in real-time.

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Grid-Based Low Computation Image Processing Algorithm of Maritime Object Detection for Navigation Aids

Cited by 3 publications

References 39 publications

RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

Intelligent Lighting System Using Color-Based Image Processing for Object Detection in Robotic Handling Applications

RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

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