Detection of wood surface defects based on particle swarm-genetic hybrid algorithm

Wood defect detection has an important influence on the automation of wood industry. In view of the complexity of wood defect segmentation, this paper proposes the hybrid algorithm of genetic algorithm and particle swarm optimization algorithm. Firstly, the contrast of the image is enhanced by the linear transformation function. Then, applying genetic algorithm and particle swarm-genetic hybrid algorithm respectively for the image segmentation, and finally morphological processing is performed. The result shows that the particle swarm-genetic hybrid algorithm has a better and more stable effect on detecting wood defects compared with the genetic algorithm.