A Novel Method of Shoe Print Recognition Based On KLT And Support Vector

Shoe print recognition is an important research field of pattern recognition. It’s a typical multi recognition problem. For a long time, it caused researchers concern from pattern recognition greatly, computer vision, and physiology, and so on. Var technology has a wide application, and various commercial Shoe print recognition systems can be applied. Feature extraction is an important part of pattern recognition, whose main p we take Principle Component Analysis (PCA) method based on algebraic statistics to extract the essential characteristics of Shoe print images. We use Support Vector Machine (SVM) as classifier. against one classification strategy for multi image. At the same time, a small Shoe print recognition system is designed. It can find Shoe print images of corresponding category from training Shoe print database when we input any Shoe print to be identified of a category.