Hydrophobic detection based on ant colony algorithm

Hydrophobicity of insulator surfaces is an important criterion of electrical performance of insulating material, and guarantees to ensure that the insulator is well operated. The key problem of measuring hydrophobicity is to detect the accurate beads (or watermarks) regions. Therefore, the ant colony algorithm (ACA) was introduced to hydrophobic image processing. First, the image was enhanced by adaptive local gray-scale balance to reduce the similarity of objectives and background caused by the transparency of water. Then, the ant colony algorithm was used to establish the perceived charts of the hydrophobic image. The water (or water traces) of the contour information was obtained using the chart information to extract the edge information. Finally, the shape factor of picture was applied to classify hydrophobic image. Experimental results show that this algorithm is efficient to hydrophobic images processing and hydrophobic images are classified accurately.