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For power transmission line detection, the multiple lasers of different wavelengths are used to location. Because of the sophisticated effects of environmental light and background elements, it's difficult to extract the laser spot. So, this paper presented a method of hybrid-laser image spot extract based on HSV space SVD for power transmission line detection, which the multiple laser spot in hybrid-laser image is formed on the target object. First, it extracts the detection spots from the hybrid-laser image. Second, it separates the detection spots at different wavelengths. Final, the paper by experiment show that this method is very effective and can accurately extract the laser spot of different wavelengths.

High voltage transmission lines have a clear and necessary straight-line feature, which can be obtained by using the method proposed in this paper to process captured images. Since high voltage transmission lines operate in a complex environment, it not only increases the noise in captured pictures, but also makes it harder to extract the transmission lines due to background interference. In order to reduce the impact of complex background and other flanking transmission lines, a novel algorithm based on opening and closing operations is proposed to facilitate extraction of the transmission lines by using the Hough transform technique. From the experiments, it is found that the novel algorithm realizes the goal of extracting the main transmission lines.

For the shockproof hammers, spacers and suspension clamps and other obstacles on 500kv high-voltage transmission lines, this article constructs the relative moment and wavelet moment of the image, and based on that, using the support vector machine (SVM) to recognize and classify these three species. Experimental results show that these two features moment can both be used to classify the target, but comparatively speaking, wavelet moment has better classification accuracy and convergence rate.