Decoupled Active Contour (DAC) for Boundary Detection

— The accurate detection of object boundaries via active contours is an ongoing research topic in computer vision. Most active contours converge towards some desired contour by minimizing a sum of internal (prior) and external (image measurement) energy terms. Such an approach is elegant, but suffers from a slow convergence rate and frequently mis-converges in the presence of noise or complex contours. To address these limitations, a decoupled active contour (DAC) is developed which applies the two energy terms separately. Essentially, the DAC consists of a measurement update step, employing a Hidden Markov Model (HMM) and Viterbi search, and then a separate prior step, which modifies the updated curve based on the relative strengths of the measurement uncertainty and the non-stationary prior. By separating the measurement and prior steps, the algorithm is less likely to mis-converge; furthermore, the use of a Viterbi optimizer allows the method to converge far more rapidly than ene...

• Type: Journal
• Year: 2011
• Where: PAMI
• Authors: Akshaya Kumar Mishra, Paul W. Fieguth, David A. Clausi
• Keywords: Active Contour, Energy Terms, Operations Research, PAMI 2011, Prior Steps