Title :
Content-based structural recognition for flower image classification
Author_Institution :
Div. of Eng., Univ. of Nottingham Ningbo China, Ningbo, China
Abstract :
Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a method of structural pattern recognition based on probabilistic based recursive model is proposed to classify flower images. Experimental results show that the developed system can yield promising results for flower image retrieval.
Keywords :
botany; content-based retrieval; image classification; image recognition; image retrieval; probability; computer-aided flower identification; content based image retrieval system; content-based structural recognition; flower image classification; flower image retrieval; plant species identification aspect; probabilistic based recursive model; structural pattern recognition; Feature extraction; Image color analysis; Image segmentation; Merging; Neural networks; Probabilistic logic; Shape; image classification; neural network; structural recognition;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-2118-2
DOI :
10.1109/ICIEA.2012.6360787
