Research on the Counting Algorithm of Bundled Steel Bars Based on the Features Matching of Connected Regions

Abstract

Aiming at the problem that tight arrangement of bundled steel bar, irregular shape of bar end surfaces, adhesions and in the automatic counting prone to multi-count and less-count, a fast and accurate counting method based on single-multi-classification of the connected regions' feature matching is proposed. Firstly, the image of the steel bars' end surface is segmented, morphological and other preprocessing to remove most of the adhesion, and then extracts the features of handled binary image including the area, diameter, center of gravity, shape factor of connected region, according to the area characteristics, the target single - Multi - Classification of the bar image target is classified, and the area feature matching of the single steel bar is counted quickly too, and according to the characteristics of the center of gravity to identify the identification of steel, multiple steel bars establish the template and combine with area, form and other factor to matching counting, so as to achieve the purpose of high efficiency and accurate counting.