DocumentCode :
49958
Title :
An Apparatus and Method for Real-Time Stacked Sheets Counting With Line-Scan Cameras
Author :
Tiejian Chen ; Yaonan Wang ; Changyan Xiao
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Volume :
64
Issue :
7
fYear :
2015
fDate :
Jul-15
Firstpage :
1876
Lastpage :
1884
Abstract :
To satisfy the requirement of quality control in printing and packaging industry, a sheet counting apparatus is developed, which adopts a line-scan camera to image the fringes of sheet stack and is able to provide a real-time and noncontact measurement of their quantity. With a brief introduction of the system architecture, our main work focuses on the sheet counting algorithms. The basic principle is to identify each sheet profile from the 1-D image with a robust ridge strength measurement. First, a multiscale bi-Gaussian ridge likelihood measurement and a ridge-valley descriptor are utilized to improve adjacent objects detection by increasing local contrast around sheet fringes. Then, a sheet recognition scheme, which integrates a peak detection algorithm and the ridge region criteria for verification, is proposed to discriminate true sheets from the obtained ridgeness measure. According to experiments and tests in real production lines, our apparatus can reach a very high measuring accuracy for printing papers or cards with a thickness not <;0.2 mm.
Keywords :
materials handling; maximum likelihood estimation; object detection; object recognition; printing industry; production engineering computing; quality control; line-scan cameras; multiscale bi-Gaussian ridge likelihood measurement; packaging industry; peak detection algorithm; printing industry; quality control; realtime stacked sheets counting; ridge region criteria; ridge-valley descriptor; ridgeness measure; robust ridge strength measurement; sheet counting algorithms; sheet counting apparatus; sheet recognition scheme; sheet stack; Algorithm design and analysis; Cameras; Kernel; Printing; Real-time systems; Standards; Bi-Gaussian kernel; machine vision; packing industry; ridge detection; sheet counting; sheet counting.;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/TIM.2014.2366977
Filename :
6963373
Link To Document :
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