A Review on Energy Minimization via Fast Approximation Algorithms
Abstract: Label cost optimization proposes a new improvement in label cost function, improving existing moves of -expansion algorithm and introducing some new moves for this algorithm. Instead of k-mean optimization algorithm new technique i. e. fast approximation can be used in -expansion algorithm to optimize label cost function. In order to perform comparison, different metrics of energy minimization will be considered. An appropriate comparison will be drawn among proposed technique and previous well known techniques. The objective is to effectively optimize energies so that satisfactory image segmentation can be obtained (represented with different labels respective to different objects).
Keywords: Energy minimization, labels, -expansion, segmentation, NP-hard, local minimum, non-parametric histogram
How to Cite?: Harsimran Kaur, Neetu Gupta, "A Review on Energy Minimization via Fast Approximation Algorithms", Volume 3 Issue 9, September 2014, International Journal of Science and Research (IJSR), Pages: 2383-2386, https://www.ijsr.net/getabstract.php?paperid=SEP14556, DOI: https://dx.doi.org/10.21275/SEP14556