Grading method of crop disease based on image processing

IFIP Advances in Information and Communication Technology

Volumn 369 AICT, Issue PART 2, 2012, Pages 427-433

  Tian, Youwen ^a   Wang, Lide ^a   Zhou, Qiuying ^a  

^a SHENYANG AGRICULTURAL UNIVERSITY   (China)

Author keywords

Computer image processing; crop disease grading; grading system

Indexed keywords

CLASSIFICATION STANDARD; COMPUTER IMAGE PROCESSING; CROP DISEASE; GRADING SYSTEM; IDENTIFICATION ACCURACY; IDENTIFICATION PRECISION; IMAGE PREPROCESSING; PAPER-CUT; SUBJECTIVE FACTORS;

GRADING; IMAGE SEGMENTATION; STRESS INTENSITY FACTORS;

CROPS;

EID: 84870572837     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-27278-3_45     Document Type: Conference Paper

References (5)

1. Mao, H., Xu, G.: Identification the deficit of tomato nutrient elements based on computer vision. Transactions of the Chinese Society for Agriculture Machinery 34, 73-75 (2003
2. Tian, Y., Li, T., Li, C., et al.: Method for recognition of grape disease based on support vector machine. Transactions of the CSAE 23, 175-179 (2007
3. Camargo, A., Smith, J. S.: Image pattern classification for the identification of disease causing agents in plants. Computers and Electronics in Agriculture 66, 121-125 (2009
4. Cen, Z., Li, B., Shi, Y., et al.: Discrimination of cucumber anthracnose and cucumber brown speck based on color image statistical characteristics. Acta Horticulturae Sinica 34, 1425-1430 (2007
5. Zhang, Z., Wang, Y., Xue, G.: Digital Image Processing and Machine Vision-Visual C++ and Matlab. People's posts and Telecommunications Press, Beijing (2010