The Transparent Capsule Defect Detection System Based On Image Processing

With the extensive application of the computer, information technology is starting to grow rapidly and play an important role in industry gradually. Meanwhile, the technology of Digital Image Processing is improving gradual. As its broad applicability, accuracy and efficiency, Digital Image Processing is taking a greater part in the industrial field. Digital Image Processing is becoming more and more important and taking and it has become inevitable to use Digital Image Processing techniques to save labor costs and reduce human errors in industrial areas.Defect detection is an important application in the field of computer vision and digital image processing. The main idea of defect detection is to find the detection image segmentation edge, and determine whether it is a fault according to the edges and the internal features. Using digital image processing techniques to identify defect detection instead of Manual inspection not only has the efficiency and stability, but also can eliminate the interference caused by human error and so on.Transparent capsule defect detection involves length, black spots, bubbles, holes, cutouts and clip wrinkle. At present, there is no perfect transparent capsule detection system in our country. This article aims to design an accurate and efficient transparent capsule defect detection system. Firstly, extract images of transporting capsule by industrial cameras. Secondly, use corrosion, histogram equalization and other initial treatments to deal with different defects. Thirdly, use improved Canny operator to extract binary edge image, and then use different defects judgment. Defective capsules will be separated in the transmission to ensure the quality of the capsules. At last, the number of qualified and unqualified capsules will be counted.The first part of this paper describes the current research status at home and abroad, the detection technology which is used and the development environment. Next, all algorithms used in the defect detection are described separately. The design and implementation of the system are described in the article. In the end, the full article is summarized, the possible optimization programs are made, and the expansion of the system discussed.