Environmental control strategies based on plant responses using intelligent machine vision technique

Computers and Electronics in Agriculture

Volumn 18, Issue 2-3, 1997, Pages 137-148

  Murase, H ^a   Nishiura, Y ^a   Mitani, K ^a  

^a Osaka Prefecture University   (Japan)

Author keywords

Computer vision; Finite element method; Image compression; Kalman filter; Neural networks

Indexed keywords

COMPUTER VISION; DIGITAL SIGNAL PROCESSING; FEATURE EXTRACTION; FEEDBACK CONTROL; FINITE ELEMENT METHOD; IMAGE COMPRESSION; KALMAN FILTERING; MOISTURE; NEURAL NETWORKS;

INTELLIGENT WATER MANAGEMENT SYSTEM; NONIVASIVE SENSING TECHNIQUE;

PLANTS (BOTANY);

EID: 0031209548     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0168-1699(97)00026-4     Document Type: Article

References (4)

1. Haralick, R.M., Shaanmugan, K., Dinstein, I., 1973. Textural features for image classification. IEEE Trans. Systems, Man, and Cybernetics, Vol. SMC-3,6,610-621.
2. Hashimoto, Y., Nonami, H., 1992. Measurement and control in transplant production systems. In: Kurata, K., Kozai, T. (Eds.), Transplant Production Systems. Kluwer, Dordrecht, pp. 117-136.
3. Murase, H., Koyama, S., Honami, N., Kuwabara, T., 1991. Kalman filter neuron training. Bull. Univ. Osaka Pref. Ser. B 43, 91-101.
4. Murase, H., Honami, N., Nishiura, Y. 1994. Image information feedback using textural features for plant growth control. Proceedings of the First Asian Control Conference, Tokyo, 27-30 July 1994, Vol. 3, pp. 17-20.