A new fast kNN classification algorithm is presented for texture and pattern recognition. The algorithm identifies the first k closest vectors in the design set of a kNN classifier for each input vector by performing the partial distance search in the wavelet domain. Simulation results show that, without increasing the classification error rate, the algorithm requires only 12.94% of the computational time of the original kNN technique.
ASJC Scopus subject areas
- Electrical and Electronic Engineering