This paper presents an algorithm for the recognition of similar electrical poles from an aerial image by detecting the pole shadow. One pole is used as a template (already identified by a human operator) for the algorithm. The algorithm includes feature extraction, candidate position determination, and elimination of redundant candidates. First, features of a pole shadow are extracted using standard filters and image processing techniques. Then the extracted features are used to design convolution filters tailored to emphasize possible locations for the shadows. Subsequently, an image candidate is submitted to Radon Transformation to verify adherence to expected shadow characteristics. Simulations show that most poles are made much more noticeable by the algorithm.

An innovative prototype sensor containing A36 carbon steel as a capacitor was explored to monitor early-stage corrosion. The sensor detected the changes of the surface- rather than the bulk- property and morphology of A36 during corrosion. Thus it was more sensitive than the conventional electrical resistance corrosion sensors. After being soaked in an aerated 0.2 M NaCl solution, the sensor’s normalized electrical resistance (R/R0) decreased continuously from 1.0 to 0.74 with the extent of corrosion. Meanwhile, the sensor’s normalized capacitance (C/C0) increased continuously from 1.0 to 1.46. X-ray diffraction result indicates that the iron rust on A36 had crystals of lepidocrocite and magnetite.

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