Abstract
Compared to color and texture, the shape is considered as an important feature for many real-time applications. In this chapter, Fuzzy Object Shape (FOS) is presented for extracting the shape information present in the images. It is further noticed that the boundary of the object is ill-defined and there is impreciseness and vagueness in the object information. The closeness of the object with well-known primitive shapes are estimated. It is known that the impreciseness can be effectively captured by fuzzy functions and FOS has offered seven fuzzy membership function for the same. The value of each fuzzy membership function are constructed as feature vector to define the properties of individual objects.
Reference20 articles.
1. Abbasi, S., Mokhtarian, F., & Kittler, J. (1999). Curvature Scale Space Image in Shape Similarity Retrieval. Multimedia Systems, (7), 467–476.
2. Fuzzy rule based profiling approach for enterprise information seeking and retrieval. Information Sciences;Alhabashneh,2017
3. Ayed, B., Kardouchi, S., & Selouani, S. A. (2012). Rotation invariant Fuzzy Shape Contexts based on Eigen shapes and Fourier transforms for efficient Radiological image retrieval. Proceedings of International Conference on Multimedia Computing and Systems (ICMCS), 26 –271.
4. Shape matching and object recognition using shape contexts
5. Supervised shape retrieval based on fusion of multiple feature spaces