Image Processing Techniques for Quality Inspection of Gelatin Capsules in Pharmaceutical Applications

Topics: Image processing, Computer vision, Digital image Pages: 20 (3798 words) Published: October 18, 2013
2008 10th Intl. Conf. on Control, Automation, Robotics and Vision Hanoi, Vietnam, 17–20 December 2008

Image Processing Techniques for Quality Inspection
of Gelatin Capsules in Pharmaceutical Applications
M.J. Islam, M. Ahmadi, M.A. Sid-Ahmed
Department of Electrical and Computer Engineering
University of Windsor, Windsor, ON, Canada
{islam1l, ahmadi,}
Abstract—Machine vision systems provide quality control and real-time feedback for industrial processes, overcoming physical limitations and subjective judgment of humans. In this paper, the image processing techniques for developing low-cost machine vision system for pharmaceutical capsule inspection is explored. By developing image processing techniques, and using PCs,

custom USB 2.0 cameras with minimal hardware, a low-cost
flexible system is developed. This paper discusses the two-part gelatin capsule inspection system that belongs to USB camera 2.0 and associated hardware, the PCs to acquire the image data of the capsule, image processing techniques using border tracing and approximating the capsule to a circle to perform inspection and a custom system controller to pass the accepted and rejected capsules to the appropriate bin.

Index Terms—Border tracing, Edge detection, Image enhancement, Segmentation, Quality inspection.

One of the most important problems, perhaps the most
urgent from the point of view of industry productivity and
competitiveness, is automatic inspection. Early detection of defects in the production means lower costs and faster feedback on the production line in order to eliminate the causes of defects, overcomes physical limitations and subjective judgment of humans. In pharmaceutical industry, zero defect quality

capsules are highly required in competitive markets. So, a very cost effective, high throughput and reliable quality inspection method is important in that industry.
Two part (body and cap) gelatin capsules are sensitive
to several common flaws that make them unacceptable for
shipment and marketing. These flaws are incorrect size or
color, dents, cracks, holes, bubbles, missing caps and so on. As consumers are demanding that products be free of defects, 100% inspection and automated inspection have to be applied
to achieve the zero-defect and at the same time to maintain
the high throughput, all defects must be detected in a single inspection. A computer vision-based quality inspection can be one solution to solve these types of problems. The main aim
of this paper is to develop a computer vision system capable of isolating defective capsules at the rate of 1000 capsules per minute with over 95% accuracy of defects of size 0.2 mm and
Currently human inspectors evaluate the quality of the capsules manufactured at most of the pharmaceutical industry. The capsules are collected in bins, each of which contains 300,000 capsules. When the inspectors find a defective capsule in one

978-1-4244-2287-6/08/$25.00 c 2008 IEEE

bin, the company discards the entire bin of capsules. This
process results in a loss of revenue, a waste of manufacturing time, increase in manufacturing costs and uncertainty about the quality of the products the company sends to the market. There are few capsule sorting machines with quality process control settings available in the market at a cost of over $500,000

per machine (eg. Viswill has a Capsules Video Inspection
Systems named CVIS-SXX manufactured in Japan, while Eisai
Machinery USA has similar Systems named CES-50,100,150).
All these systems are very expensive and most of them use
existing vision system such as cognex. Hence, the objective is to develop a low cost computer vision-based quality inspection system that can provide high throughput, reliability and obviously zero defect quality product. A computationally efficient image processing techniques is a required addition to the lowcost hardware systems to perform the quality inspection...
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