An Image Retrieval Method Based on r/KPSO
Xu Zhang, Baolong Guo, Guiyue Zhang, Yunyi Yan · 2011
Image retrieval is a hot and hard technology in the field of computing science. In this paper, a method named r/KPSO (Particle Swarm Optimization with r- and K-selection) is applied in relevance feedback (RF) of image retrieval. The main idea of r/KPSO is inspired by the r- and K-selection of Ecology. r-selection can be characterized as: quantitative, little parent care, large growth rate and rapid development and K-selection as: qualitative, much parent care, small growth rate and slow development. Based on r/KPSO, we define the positive and negative feedback samples as study principle, and optimize weightings according to user's retrieval requirement. Experiments show that both the recall and precision are improved effectively.