A Character Validation Proposal for High-Speed Visual Monitoring of Expiration Codes on Beverage Cans

Abstract

Character recognizers have generally focused on printed text on paper with an emphasis on generality rather than speed. This makes the proposed algorithms not applicable in the context of the very high-speed industrial validation of expiration codes printed on the metal surface of a can. The extreme demands of speed and the adverse effects of lighting and movement, among other things, make it necessary to develop an original and specific strategy. The strategy presented in this paper first selects which of the segmented shapes of a printed can are the best candidates for comparison with expected characters. This is followed by a technique based on the comparison of templates (templates matching), which we call “morphologies”, and are represented as bitmaps to take advantage of the hardware capabilities of general-purpose processors. The use of templates has the advantage of avoiding the construction of a feature vector. In an acquisition test in a real industrial plant, we have been able to successfully treat 438 cans in 44 s, with only one validation error in one character, achieving a compromise between speed and quality that is sufficient for industrial validation in the conditions cited.

A Very High-Speed Validation Scheme Based on Template Matching for Segmented Character Expiration Codes on Beverage Cans

“…This paper expands upon a previous publication [1] and is the natural continuation of an earlier study [2] which presented an industrial validator of expiration codes printed on aluminium or tin cans, called MONICOD.…”

“…Note that the expiration codes may be arranged on one or more lines. This novel procedure for assigning fragments to bands is described in [1]. It is based on agents that simultaneously navigate the image looking for line spacing in the segmented text.…”

“…(3) Start of the learning cycle for the current can. (4) The procedure described in [1] is applied until the true code is attained. (5) For each of the expected characters, the corresponding shape (by position) is extracted from the true code obtained and the MFD is consulted for the associated morphological family.…”

“…However, of these 27 wrongly validated cans only one can (0.21%) was caused by the system described in this paper. The rest of the wrongly validated cans were due to errors in the elliptical histogram algorithm, band division and ink fragment grouping (see [1,6,7]).…”