Image Algorithm of Ship Detection for Surface Vehicle

Jing Fang; Shun Shan Feng; Yuan Feng

doi:10.15918/j.tbit1001-0645.2017.12.005

Image Algorithm of Ship Detection for Surface Vehicle

Jing Fang, Shun Shan Feng^*, Yuan Feng

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

In order to solve the problem that the surface vehicle detecting ship targets in the nearshore waters was vulnerable to light, similar color background and wave reflection, ship detection algorithm based on improved visual attention model was proposed. First, low frequency and high frequency features of images were extracted by using wavelet transform theory. Then, the hue, saturation and value features of images were also extracted by converting the images of task waters from RGB color space to HSV color space. Finally, various features of images were merged in the application of image processing method of Gaussian Pyramid and normalization operator. The simulation results show that the proposed ship detection method can accurately detect the ship targets under complicated backgrounds and has satisfactory anti-interference capability.

Original language	English
Pages (from-to)	1235-1240
Number of pages	6
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	37
Issue number	12
DOIs	https://doi.org/10.15918/j.tbit1001-0645.2017.12.005
Publication status	Published - 1 Dec 2017
Externally published	Yes

Keywords

Ship detection
Surface vehicle
Visual attention
Wavelet transform

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10.15918/j.tbit1001-0645.2017.12.005

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title = "Image Algorithm of Ship Detection for Surface Vehicle",

abstract = "In order to solve the problem that the surface vehicle detecting ship targets in the nearshore waters was vulnerable to light, similar color background and wave reflection, ship detection algorithm based on improved visual attention model was proposed. First, low frequency and high frequency features of images were extracted by using wavelet transform theory. Then, the hue, saturation and value features of images were also extracted by converting the images of task waters from RGB color space to HSV color space. Finally, various features of images were merged in the application of image processing method of Gaussian Pyramid and normalization operator. The simulation results show that the proposed ship detection method can accurately detect the ship targets under complicated backgrounds and has satisfactory anti-interference capability.",

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author = "Jing Fang and Feng, {Shun Shan} and Yuan Feng",

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T1 - Image Algorithm of Ship Detection for Surface Vehicle

AU - Fang, Jing

AU - Feng, Shun Shan

AU - Feng, Yuan

PY - 2017/12/1

Y1 - 2017/12/1

N2 - In order to solve the problem that the surface vehicle detecting ship targets in the nearshore waters was vulnerable to light, similar color background and wave reflection, ship detection algorithm based on improved visual attention model was proposed. First, low frequency and high frequency features of images were extracted by using wavelet transform theory. Then, the hue, saturation and value features of images were also extracted by converting the images of task waters from RGB color space to HSV color space. Finally, various features of images were merged in the application of image processing method of Gaussian Pyramid and normalization operator. The simulation results show that the proposed ship detection method can accurately detect the ship targets under complicated backgrounds and has satisfactory anti-interference capability.

AB - In order to solve the problem that the surface vehicle detecting ship targets in the nearshore waters was vulnerable to light, similar color background and wave reflection, ship detection algorithm based on improved visual attention model was proposed. First, low frequency and high frequency features of images were extracted by using wavelet transform theory. Then, the hue, saturation and value features of images were also extracted by converting the images of task waters from RGB color space to HSV color space. Finally, various features of images were merged in the application of image processing method of Gaussian Pyramid and normalization operator. The simulation results show that the proposed ship detection method can accurately detect the ship targets under complicated backgrounds and has satisfactory anti-interference capability.

KW - Ship detection

KW - Surface vehicle

KW - Visual attention

KW - Wavelet transform

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Image Algorithm of Ship Detection for Surface Vehicle

Abstract

Keywords

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