E. Bayro-Corrochano and E. Hancock (Eds.): CIARP 2014, LNCS 8827, pp. 1014–1021, 2014. © Springer International Publishing Switzerland 2014 Comparative Evaluation of Edge Linking Methods Using Markov Chain and Regression Applied Heuristic Haklin Kimm, Neda Abolhassani, and Eun-Joo Lee Computer Science Department East Stroudsburg University of Pennsylvania East Stroudsburg, PA, USA {hkimm,elee}@po-box.esu.edu Abstract. There have been many studies on how to develop accurate edge detection algorithms for various applications – especially processing geographic images and maps, say coastline images. In this paper, we present edge linking algorithms, based on a heuristic approach using regression analysis and Markov chain technique respectively, for the coastline images. The heuristic approach consists of costs that are based on the distance and direction of the edge terminators while the Markov chain technique has been developed to investigate possible line drawing options to reconnect the broken edges so that a Markov transition matrix is generated in order to find the suitable edge terminators that can be reconnected. In this paper both techniques of using Markov chain and regression analysis have been developed and their outcomes have been evaluated comparatively upon their accuracy of reconnecting the broken edges. Keywords: Edge detection and linking, Markov Chains, Regression based heuristic, Image Processing, Coastline images. 1 Introduction Edges are considered as one of the most significant features of an image. Many of the edge detectors work based on the gradient at an edge point and the direction of the edge on that point [1], [2]. Conventional edge detectors have some problems due to differentiation functions and noises in an image. The source for the noise problem in coastline detection of satellite images can be clouds or other objects that result in an unclear image of the position of ocean and nearby land area [3], [4]. There have been various edge detection algorithms such as Prewitt, Sobel, Canny and Morphological that have been applied to the coastal satellite images [5]. In this paper, we present edge linking algorithms based on a heuristic function using regression analysis and Markov chain technique respectively. The heuristic approach, say function, consists of costs which are based on the distance and direction of the edge terminators. The proposed heuristic function is explained in detail with its regression analysis technique in later section; and followed by Markov chain technique for reconnecting edges [6], [7]. Due to presence of non-continuous edges in the coastline images of edges, this work first implements an edge linking method which is based on Markov transition