Ear Recognition Based on Locally Linear Embedding and Its Improved Algorithm
Fulin Luo · Guangdian gongcheng · 2012
Through the analysis of the disadvantages of early ear recognition methods, Locally Linear Embedding (LLE) algorithm is employed to deal with ear recognition. However, LLE algorithm depends heavily on the number K of close neighbors points. Usually, K is large in order to get a good dimensionality reduction effect, while the computational complexity increases. In order to weaken the algorithm’s dependence on K, the LLE algorithm was improved, which made the sample set be more evenly distributed. Even if a smaller number K was selected, the improved LLE algorithm could still get a good dimension reduction effect, and expand the range of K to some extent. Ear recognition contrast experiments of the improved LLE algorithm and the original LLE algorithm show that the improved LLE can obtain a higher recognition rate, thus verify the efficiency of the improved LLE algorithm.