Parallel extended local feature extraction on distributed memory computer

Feature extraction is the most important phase in object recognition because accuracy of the system relies on how well the features are extracted. In this paper a new parallel extended local feature extraction method is proposed which can be implemented on a distributed memory machine. In order to reduce the complexity in the extended local feature extraction, an efficient algorithm is developed which is capable of exploiting a high degree of parallelism. Our parallel algorithm is implemented and tested on an Intel iPSC/2 hypercube computer. Some resulting figures and execution times according to various number of nodes and object features are presented