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SAS image segmentation method and system based on SVM classifier

An image segmentation and classifier technology, which can be used in image analysis, image data processing, instruments, etc., and can solve problems such as difficult image segmentation.

Inactive Publication Date: 2013-12-04
INST OF ACOUSTICS CHINESE ACAD OF SCI
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  • Claims
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Problems solved by technology

However, due to the influence of coherent speckle noise (Speckle), image segmentation has always been a difficult problem in SAS image processing and analysis.

Method used

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  • SAS image segmentation method and system based on SVM classifier
  • SAS image segmentation method and system based on SVM classifier
  • SAS image segmentation method and system based on SVM classifier

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Embodiment

[0154] In the present invention, the synthetic aperture sonar image obtained by a certain lake test is used for algorithm verification, and the SAS image SVM segmentation process is as follows figure 1 Shown. First select the training image, such as Image 6 As shown, the bottom area is composed of flooded farmland and river channels. The upper part of this training SAS image is the submerged terraces, the sediment type is mud, and the lower part is the river, and the sediment type is sand. Since SVM is a supervised machine learning method, it is necessary to manually extract image features as SVM training data.

[0155] Such as Figure 7 As shown, red and green respectively represent the two manually segmented regions. Red indicates the upper farmland area, which is mainly composed of muddy bottom and the topography changes drastically. Green indicates the lower channel area, which is mainly composed of sandy bottom areas, and the terrain is relatively flat.

[0156] After the ...

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Abstract

The invention discloses an SAS image segmentation method and system based on an SVM classifier. The method comprises the steps of (101) pre-processing an SAS image to be segmented to acquire grey level histograms and grey level co-occurrence matrices of different areas of the SAS image; (102) extracting a plurality of statistical property parameters from the grey level histograms and a plurality of textural feature parameters from the grey level co-occurrence matrices; (103) inputting the statistical property parameters and the textural feature parameters into the SVM classifier to carry out segmentation on the SAS image to be segmented, wherein the SVM classifier is obtained through training by taking a plurality of statistical property parameters extracted from a grey level histogram of a certain area of the training image and a plurality of textural feature parameters extracted from a grey level co-occurrence matrix of the certain area of the training image as training features; (104) optimizing segmented images output from step (103) by means of mathematical morphology operators so that cavities and isolated points in the segmented images can be removed.

Description

Technical field [0001] The invention relates to an image segmentation method based on a synthetic aperture sonar image, and specifically proposes a SAS image segmentation method and system based on an SVM classifier. Background technique [0002] Synthetic Aperture Sonar (SAS, Synthetic Aperture Sonar) is a high-resolution underwater imaging sonar that can obtain high-quality underwater image data. Synthetic aperture is a technology that can significantly improve azimuth resolution without a long receiving array. Synthetic aperture sonar can obtain images with high azimuth resolution and range resolution through this technology and complex imaging algorithms. It has high value in the field of underwater research. Compared with ordinary sonar, synthetic aperture sonar improves the array aperture through the linear movement of the base array. In principle, the resolution of the synthetic aperture sonar image has nothing to do with the working frequency and operating distance, so i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62G06V10/764G06V20/13
CPCG06V20/13G06V10/54G06V10/764
Inventor 陈强田杰刘维黄海宁张春华
Owner INST OF ACOUSTICS CHINESE ACAD OF SCI
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