Particle Swarm Optimization for Object Recognition in Computer Vision
作者： Hugo A. Perlin , Heitor S. Lopes , Tânia Mezzadri Centeno
DOI: 10.1007/978-3-540-69052-8_2
关键词:
摘要: Particle Swarm Optimization (PSO) is an evolutionary computation technique frequently used for optimization tasks. This work aims at applying PSO recognizing specific patterns in complex images. Experiments were done with gray level and color images, without noise. was able to find predefined reference submitted translation, rotation, scaling, occlusion, noise change the viewpoint landscape image. Several experiments evaluate performance of PSO. Results show that proposed method robust very promising real-world applications.
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