Detecting textured objects using convex hull

In this paper, we present a methodology of locating 3D objects of known shapes from a single gray-scale image, in particular objects with rich textures on the surface. While traditional approaches identify objects by grouping and matching local features, we locate the object in the image using its convex hull, a high level feature not given much attention in the image using literature. A “direct line detection” algorithm is developed to detect line segments directly from the gray-scale image divided in small blocks. Lines are clustered and convex hull of a single or group of clusters is computed and edited to extract the 2D contour of the object. Successful experiments on rectangular boxes and cylinders show the effectiveness of the convex hull approach and its potential usage in industrial applications.