Next Article in Journal
An Improved Study of Multilevel Semantic Network Visualization for Analyzing Sentiment Word of Movie Review Data
Next Article in Special Issue
Use of Texture Feature Maps for the Refinement of Information Derived from Digital Intraoral Radiographs of Lytic and Sclerotic Lesions
Previous Article in Journal
Sound Source Localization Fusion Algorithm and Performance Analysis of a Three-Plane Five-Element Microphone Array
Open AccessArticle

Machine Vision System for Counting Small Metal Parts in Electro-Deposition Industry

Department of Industrial Engineering, University of Florence, 50134 Firenze, Italy
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(12), 2418; https://doi.org/10.3390/app9122418
Received: 20 May 2019 / Revised: 12 June 2019 / Accepted: 13 June 2019 / Published: 13 June 2019
(This article belongs to the Special Issue Texture and Colour in Image Analysis)
In the fashion field, the use of electroplated small metal parts such as studs, clips and buckles is widespread. The plate is often made of precious metal, such as gold or platinum. Due to the high cost of these materials, it is strategically relevant and of primary importance for manufacturers to avoid any waste by depositing only the strictly necessary amount of material. To this aim, companies need to be aware of the overall number of items to be electroplated so that it is possible to properly set the parameters driving the galvanic process. Accordingly, the present paper describes a simple, yet effective machine vision-based method able to automatically count small metal parts arranged on a galvanic frame. The devised method, which relies on the definition of a rear projection-based acquisition system and on the development of image processing-based routines, is able to properly count the number of items on the galvanic frame. The system is implemented on a counting machine, which is meant to be adopted in the galvanic industrial practice to properly define a suitable set or working parameters (such as the current, voltage, and deposition time) for the electroplating machine and, thereby, assure the desired plate thickness from one side and avoid material waste on the other. View Full-Text
Keywords: Machine vision; image analysis; item counting device; electro-deposition industry Machine vision; image analysis; item counting device; electro-deposition industry
Show Figures

Graphical abstract

MDPI and ACS Style

Furferi, R.; Governi, L.; Puggelli, L.; Servi, M.; Volpe, Y. Machine Vision System for Counting Small Metal Parts in Electro-Deposition Industry. Appl. Sci. 2019, 9, 2418.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop