Signal and Data Processing

In this paper, a novel shape descriptor for shape-based object retrieval is proposed. A growing process is introduced in which a contour is reconstructed from the bounding circle of the shape. In this growing process, circle points move toward the shape in normal direction until they  get to the shape contour. Three different shape descriptors are extracted from this process: the first descriptor is defined as the number of steps that every circle point should pass which is called Growing Steps. The second descriptor is considered as the boundary distance of the circle points at the end of the growing process. The third descriptor is the curvature of the growing lines created by moving points. Invariance to translation is the intrinsic property of these features. By selecting a fixed starting point and tracing the boundary in a fixed direction (clock-wise or  counter clock-wise), a set of descriptors  could be collected invariant to rotation. Finally, normalizing the descriptors makes them invariant to scale. Support vector machines based on one-shot score are applied in the retrieval stage. Experimental results show that the suggested method has high performance for shape retrieval. It achieves 89.16% retrieval rate on MPEG-7 CE-Shape-1 dataset.