Research on visual significance detection of small cracks in ship turbine blades
To accurately grasp the operating status of turbine blades and determine whether they need to be replaced,a visual significance detection method for small cracks in ship turbine blades is proposed.Using an improved homomorphic filtering algorithm to smooth the blade CCD image,enhance the contrast and balance of the image,extract saliency maps based on spectral residual visual attention model,segment the saliency maps obtained through linear iterative clustering al-gorithm,set the judgment threshold,determine the final small crack area of the ship turbine blade,and complete the detec-tion of small cracks in the ship turbine blade.The test results show that this method has good application effects and can sig-nificantly improve the overall uniformity of the image;The extraction effect of saliency maps is good,with an average abso-lute error below 0.021,which reliably determines the small crack areas of ship turbine blades.
ship turbinesmall cracks in the leavesvisual saliency detectionimage processing
NETL
NSTL
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