Abstract-We present ratio contour, a novel graph-based method for extracting salient closed boundaries from noisy images. This method operates on a set of boundary fragments that are produced by edge detection. Boundary extraction identifies a subset of these fragments and connects them sequentially to form a closed boundary with the largest saliency. We encode the Gestalt laws of proximity and continuity in a novel boundary-saliency measure based on the relative gap length and average curvature when connecting fragments to form a closed boundary. This new measure attempts to remove a possible bias toward short boundaries. We present a polynomial-time algorithm for finding the most-salient closed boundary. We also present supplementary preprocessing steps that facilitate the application of ratio contour to real images. We compare ratio contour to two closely related methods for extracting closed boundaries: Elder and Zucker's method based on the shortest-path algorithm and Williams and Thornber's method based on spectral analysis and a strongly-connected-components algorithm. This comparison involves both theoretic analysis and experimental evaluation on both synthesized data and real images.

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The integrity of the electric power cables is vital to the safety of an entire electrical system. To ensure the health of the cables, a technique is needed for both detecting/locating defects, and predicting hard defects before they occur. The theory and limitations of the classical wiring diagnostic techniques time domain reflectometry (TDR) and frequency domain reflectometry (FDR) are discussed. This study then introduces joint time-frequency domain reflectometry (JTFDR) as a unique solution for the cable diagnostics and prognostics. By employing an interrogating incident signal and advanced post-processing of the reflected signals, JTFDR is shown to be capable of overcoming those limitations. JTFDR is experimentally proven to be successful for detecting and locating both hard and incipient defects. The prognostic capabilities of JTFDR are also demonstrated via accelerated ageing tests of an electric power cable. In conclusion, by utilising the incident/ reflected signal information in the time and frequency domains simultaneously, JTFDR is proven to be a more effective diagnostic technique than the classical TDR and FDR. JTFDR can also be used to monitor incipient defects and better predict hard defects before they occur.

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