Crysdian, C & Nugroho, BA. (2016). A Framework for Optimum Contour Detection. The Joint International Conference of the 3rd International Conference on Nano Electronics & Research Education and the 8th Internatioanl Conference on Electrical Power, Electronics, Communication, Controls & Informatics System (ICNERE-EECCIS) 2016.
Abstract
The importance of contour detection have been acknowledged by researchers worldwide, and indeed dozens of methods have been introduced. However there is no single method suit with various conditions of digital images. Most of the time, a tedious work to select best method from dozens is required only to derive the most appropriate objects contour from a digital image. Once an object contour is recognized, further image analysis process can be computed efficiently. This condition is in contrast with human visual perception which employs contour detection as a preliminary process with minimal energy consumption before conducting exhaustive visual analysis. Therefore this research aims to develop a framework to automatically detecting optimum object contour by selecting the best method for each condition of input image. Efficient energy consumption will be achieved by applying mechanism based on multi criteria decision making.