Title :
A Method of Fruits Recognition Based on SIFT Characteristics Matching
Author :
Song Wan-gan ; Guo Hong-Xia ; Wang Yan
Author_Institution :
Sch. of Comput. Sci. & Technol., Huaibei Coal Ind. Teachers´ Coll., Huaibei, China
Abstract :
SIFT (scale invariant feature transform) used in fruits recognition presents a characteristics matching algorithm according to fruits images. The algorithm uses SIFT characteristics as matching feature, then introduces Euclidean distance as the similarity metrics of image matching, and uses a method of setting a threshold value to delete the false matching points. The experimental results prove that the algorithm can effectively solve the problem of fruits recognition and matching with translation, rotation, scaling, and partial occlusion.
Keywords :
image matching; object recognition; transforms; Euclidean distance; SIFT characteristics matching algorithm; feature extraction; fruits recognition; image matching; matching feature; scale invariant feature transform; similarity metrics; Character recognition; Educational institutions; Feature extraction; Image matching; Image processing; Image recognition; Image registration; Lighting; Machine vision; Noise robustness; Feature Extraction; Feature Matching; Scale Invariant Feature Transform; Work-piece Recognition;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.484
