Automated defect detection for Fluorescent Penetrant Inspection using Random Forest

Automated Defect Inspection Systems by Pattern Recognition

Visual inspection and classification of cigarettes packaged in a tin container is very important in manufacturing cigarette products that require high quality package presentation. For accurate automated inspection and classification, computer vision has been deployed widely in manufacturing. We present the detection of the defective packaging of tins of cigarettes by identifying individual obj...

Engineering studies for fluorescent penetrant inspection with a focus on developer application methods

Corrosion Detection for Automated Visual Inspection

Defect Detection Using Hidden Markov Random Fields

We derive an approximate maximum a posteriori (MAP) method for detecting NDE defect signals using hidden Markov random fields (HMRFs). In the proposed HMRF framework, a set of spatially distributed NDE measurements is assumed to form a noisy realization of an underlying random field that has a simple structure with Markovian dependence. Here, the random field describes the defect signals to be ...

Automated Fabric Defect Inspection for Quality Assurance Systems

Existent industrial applications of computer vision systems are directly connected to quality assurance requirements. The task of fabric defect detection is carried out by human visual inspection, in most of the traditional textile industry. The possibility of automated defect detection is investigated and a solution leading to improved productivity and high quality in the weaving process is pr...