Particle swarm optimization-based optimal real Gabor filter for surface inspection

Abstract

Purpose The traditional methods have difficulty to inspection various types of copper strips defects as inclusions, pits and delamination defects under uneven illumination. Therefore, this paper aims to propose an optimal real Gabor filter model for inspection; however, improper selection of Gabor parameters will cause the boundary between the defect and the background image to be not very clear. This will make the defect and the background cannot be completely separated. Design/methodology/approach The authors proposed an optimal Real Gabor filter model for inspection of copper surface defects under uneven illumination. This proposed method only requires a single filter by calculating the specific convolution energy of the Gabor filter with the image. The Real Gabor filter’s parameter is optimized by particle swarm optimization (PSO), which objective fitness function is maximization of the Gabor filter’s energy average divided by the energy standard deviation, the objective makes a distinction between the defect and normal area. Findings The authors have verified the effect with different iterations of parameter optimization using PSO, the effects with different control constant of energy and neighborhood window size of real Gabor filter, the experimental results on a number of metal surface have shown the proposed method achieved a well performance in defect recognition of metal surface. Originality/value The authors propose a defect detection method based on particle swarm optimization for single Gabor filter parameters optimization. This proposed method only requires a single filter and finds the best parameters of the Gabor filter. By calculating the specific convolution energy of the Gabor filter and the image, to obtain the best Gabor filter parameters and to highlight the defects, the particle swarm optimization algorithm’s fitness objective function is maximize the Gabor filter's average energy divided by the energy standard deviation.

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

“…If Gabor parameters are not selected properly, the boundaries between the defects and the background are not very clear, which will make the defect and background unable to be completely separated. In view of this situation, Wu adopted a Gabor filter model [ 75 ] that is optimal and practical under uneven illumination conditions for copper surface defect detection. Similarly, to avoid this parameter selection problem, Tolba et al [ 76 ] developed a new image visual quality measurement method based on a multi-scale structure similarity index, which not only has scale invariance but also achieves high detection accuracy and quasi-real-time processing speed.…”

Defects Prediction Method for Radiographic Images Based on Random PSO Using Regional Fluctuation Sensitivity

“…For instance, in a study on leather defect detection, a modified fitness function using selective-band Shannon entropy improved segmentation efficiency [ 25 ]. The velocity setting also influences algorithm convergence and search efficiency [ 26 ]. Balancing exploration and exploitation behaviors, the velocity should facilitate effective solution space exploration without being trapped in local optima.…”

Simulation of Fatigue Fracture Detection of Bridge Steel Structures under Cyclic Loads

“…At present, there are three main fatigue design methods, the first is the infinite life design, which is a simplified design method, which requires the design stress of the structure lower than its fatigue limit stress value; S - N curve (stress-fatigue life curve) reflects the relationship between fatigue strength and fatigue life of the specimen under cyclic loading, according to the bridge design after knowing the stress amplitude S , according to the stress-fatigue. Based on the S - N curve, some scholars have proposed a safe life design to ensure that the member or connection can be used normally within the safe service life: damage tolerance design based on fracture mechanics to ensure that the damage will not be caused by crack expansion during the trial period by estimating its remaining life [ 12 ].…”