Title :
The automatic classification of the agricultural products based on the wavelet texture analysis
Author_Institution :
Inf. Sci. & Technol. Coll., Hunan Agric. Univ., Changsha, China
Abstract :
The paper puts forward a technology for the agricultural products automatic identification based on the wavelet texture analysis. The experiment chooses different levels of four apples, extracting their wavelet texture features and then classifying their features. The experiment shows that the technology has smaller computing complexity and higher stability for the product change whose products have the same kind but different classifications.
Keywords :
agricultural products; computational complexity; feature extraction; image classification; image texture; wavelet transforms; agricultural products automatic identification; apples; automatic classification; computing complexity; features classification; product change; wavelet texture analysis-based agricultural products; wavelet texture features extraction; Joints; Noise; Vectors; Watermarking; automatic identification; multi-scale wavelet; texture analysis;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182542