Shape defect estimation based on closed curve convex hull

Abstract

Shape representation is a well-researched domain, which plays an important role in many applications ranging from image analysis and pattern recognition to computer graphics and computer animation. Therefore, many methods for shape representation exist in the literature. One of the techniques for shape representation is based on convex hull. The convex hull of a shape is the smallest polygon that positions the entire points of the input shape within the polygon [1]. In this work, a starfruit shape defect estimation technique based on convex hull is presented. The aim is to transform the input shape into convex hull with better efficiency compared to the previous technique. Based on the resulting convex hull, the shape defect of the starfruit will be quantified. The convex hull algorithm has been introduced as early as 1972 by Graham [10]. Then, few other algorithms have been introduced [3, 4]. The problem with these early-introduced algorithms is their low computational efficiency because of the involvement of sorting process of the input points. Sorting the input points consumes O(n log n) running time and it is less memory efficient, as it requires an extra temporary array. After the sorting process, the algorithm employs a stack-based method to form the convex hull, which runs in just O(n) time.