A REVIEW OF VISION BASED DEFECT DETECTION USING IMAGE PROCESSING TECHNIQUES FOR BEVERAGE MANUFACTURING INDUSTRY
Author(s) -
Nor Nabilah Syazana Abdul Rahman,
Norhashimah Mohd Saad,
Abdul Rahim Abdullah,
Norunnajjah Ahmat
Publication year - 2019
Publication title -
jurnal teknologi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.191
H-Index - 22
eISSN - 2180-3722
pISSN - 0127-9696
DOI - 10.11113/jt.v81.12505
Subject(s) - standardization , quality (philosophy) , manufacturing , container (type theory) , visual inspection , computer science , manufacturing engineering , control (management) , product (mathematics) , scale (ratio) , machine vision , engineering , artificial intelligence , business , marketing , mechanical engineering , philosophy , geometry , mathematics , epistemology , operating system , physics , quantum mechanics
Vision based quality inspection emerged as a prime candidate in beverage manufacturing industry. It functions to control the product quality for the large scale industries; not only to save time, cost and labour, but also to secure a competitive advantage. It is a requirement of International Organization for Standardization (ISO) 9001, to appease the customer satisfaction in term of frequent improvement of the quality of products and services. It is totally impractical to rely on human inspector to handle a large scale quality control production because human has major drawback in their performance such as inconsistency and time consuming. This article reviews defect detection using image processing techniques for beverage manufacturing industry. There are comparative studies on techniques suggested by previous researchers. This review focuses on shape defect detection, color concentration inspection and level of liquid products measurement in a container. Shape, color and level defects are the main concern for bottle inspection in beverage manufacturing industry. The development of practical testing and the services performance are also discussed in this paper.
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