Method for railway car numbers block recognition based on committee neuroimmune classification

Abstract

Method for railway car numbers block recognition based on committee neuroimmune classification

I.S. Artemyev, A.I. Lebedev, A.I. Dolgiy, A.E. Khatlamadzhiyan, V.D. Meerovich

Incoming article date: 11.02.2014

This paper presents a new neuroimmune-based method for block recognition of railway rolling stock inventory numbers. The advantage of such approach is  classification without using of negative samples. Developed technique combines segmentation and classification that allows to achieve higher noise robustness, segmentation possibility of fuzzy combined digits which have different fonts and typeface, and invariance of existing numbers to scale changes. Proposed method allows to constantly increase the training set for the improvement in classification accuracy by new committee classifiers statistics due to the data reduction property achieved by using the immune clustering mechanism. Research results were implemented in the software system of automatic recognition of cars numbers (ARNV), which is operated on the JSC Russian Railways.

Keywords: Method for letters block recognition, the committee neuroimmune classification model, identification, automatic recognition car number, duplicate number