Comparative Study on Plant Feature Detection Algorithms Based Content
Rong Fei, Cheng Naike, Wang zhanmin, Aimin Li, Li Shasha · 2018
Recently, CBIR (context based image retrieval) which is applied in species conservation for plants, is applied in a variety of industries by many botanists and other experts. Great varieties for plants and diversity from the change of time and space make the problem become complex. In this paper, an image retrieval system of plants based context is constructed, which extracts color, shape and texture features from images of plants to compute the similarity distance, and then, related image results can be provided by sorting the similarity distance. Four algorithms is analyzed in experiments, the results show that the algorithm based texture extraction has strong retrieval robustness.