Panoramic Sea-Sky-Line Detection Based on Improved Active Contour Model

Su, Li; Wu, Junjie; Pang, Di

doi:10.3788/aos201636.1115003

Cited by 1 publication

(2 citation statements)

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“…Several feature detectors and descriptors can be combined to obtain robust illumination enhancement or sea-skyline detection [24]. Some algorithms use a combination of Canny edge detection and the Hough transform to detect the sea-skyline; this approach has strong robustness [15,16,25,26]. However, these algorithms are designed for images taken by an infrared camera or a perspective camera.…”

Section: Introductionmentioning

confidence: 99%

“…Many DIS methods have been proposed, such as the block-based method [10][11][12][13], the sub-image phase correlation-based method [14], the feature-based method [15,16], the bit-plane-based method [17,18], the gray projection-based method [19], and the seaskyline-based method [20]. However, these stabilization methods are global motion compensation-based methods for perspective imaging, which cannot be used to correct the deformations in panoramic images for the following reasons.…”

Section: Introductionmentioning

confidence: 99%

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Sea-skyline-based image stabilization of a buoy-mounted catadioptric omnidirectional vision system

Cai

Weng

Zhu

2018

J Image Video Proc.

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Marine monitoring systems have the requirements of a large field of view, low power consumption, real-time viewing, and economical and automatic functionality. This paper establishes an omnidirectional vision system used in marine buoys that meets these requirements. We present a framework for image stabilization, which is achieved by omnidirectional sea-skyline detection in a marine environment. We propose an optimal edge estimation method to calculate the sea-skyline ellipsis according to the sea-skyline characteristics in panoramic images. We construct a compact panoramic image stabilization model based on the sea-skyline and propose a reconstruction method for the invalid regions using the key frame. The experimental results and analysis show that the proposed approach is capable of acquiring stable video in real-time marine monitoring tasks and that the target detection is sufficiently effective, efficient, and accurate for a real-time ship target detection application.

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