655 – Advances in Statistical Image Analysis
An Application of Spatial Point Process
Kalanka Jayalath
Stephen F. Austin State University
Richard F. Gunst
Southern Methodist University
David J. Meltzer
Southern Methodist University
Identifying spatially distributed point patterns plays an important role in many scientific areas including pattern recognition, computer vision, image processing and some geological applications. This research is focused on applying spatial point process theories to analyze suspected prehistoric house structures belongs to Pleistocene people. Various statistical methods such as quadrat method, cluster indices and Ripley's K function are used to test the complete spatial randomness of rock locations of the excavated sites. A variation of the K-function known as the L-function is used to compare the clustering structures identified in few different sites and the existence of small scale regularities of those sites is also discussed.