This paper introduces the minimal local reconstruction error (MLRE) as a similarity measure and presents a MLRE-based classier. From the geometric meaning of the minimal local reconstruction error, we derive that the MLRE-based classifier is a generalization of the conventional nearest neighbor classier and the nearest neighbor line and plane classifiers. We further apply the MLRE measure to characterize the within-class and between-class local scatters and then develop a MLRE measure based discriminant feature extraction method. The proposed MLRE-based feature extraction method is in line with the MLRE-based classification method in spirit, thus the two methods can be seamlessly combined in applications. The experimental results on the CENPARMI handwritten numeral database and the FERET face image database show effectiveness of the proposed MLRE-based feature extraction and classification method.

In this paper, the integrated probability function (IPF) on local mean distance for image recognition was proposed to combine features for the best performance. Experiments were performed on CENPAMI handwriting digit database. The IPF on local mean distance was shown to be a good combination method for image recognition.

In Chinese, thousands of bankchecks are validated due to manual processing every day to find out the bankchecks, which are invalidate to the bank's rules or contain error input information. It is necessary to relieve people from these intensive and tedious works. This paper presents a technique, which is the preprocess stage in our auto-validating system, for extracting the user-entered courtesy amount item from Chinese bankcheck images. Seal imprints in different types and positions cause the main difficulty in the extracting procedure. Instead of removing lines in bi-level images, we proposed a line removal algorithm based on crossing shape analysis in gray-level image. The handwritten information is extracted by a new recursive thresholding algorithm, which can continue removing the brighter background until only the darkest object is left. The proposed methods have been evaluated on real-life Chinese checks. And the results demonstrate the effectiveness of the proposed preprocessing techniques.