Feasibility Study on Plant Chili Disease Detection Using Image Processing Techniques

Producing chili is a daunting task as the plant is exposed to the attacks from various micro-organisms and bacterial diseases and pests. The symptoms of the attacks are usually distinguished through the leaves, stems or fruit inspection. This paper discusses the effective way used in performing early detection of chili disease through leaf features inspection. Leaf image is captured and processed to determine the health status of each plant. Currently the chemicals are applied to the plants periodically without considering the requirement of each plant. This technique will ensure that the chemicals only applied when the plants are detected to be effected with the diseases. The image processing techniques are used to perform hundreds of chili disease images. The plant chili disease detection through leaf image and data processing techniques is very useful and inexpensive system especially for assisting farmers in monitoring the big plantation area.

[1]  Daniel Snow,et al.  Signfinder: using color to detect, localize and identify informational signs , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[2]  Xiaofeng Wang,et al.  Shape Recognition Based on Radial Basis Probabilistic Neural Network and Application to Plant Species Identification , 2005, ISNN.

[3]  Ingeborg Tastl,et al.  Transforming an analytically defined color space to match psychophysically gained color distances , 1998, Electronic Imaging.

[4]  Brian V. Funt,et al.  Color Constant Color Indexing , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[6]  D. F. Specht,et al.  Probabilistic neural networks for classification, mapping, or associative memory , 1988, IEEE 1988 International Conference on Neural Networks.

[7]  Erik Reinhard,et al.  Color Transfer between Images , 2001, IEEE Computer Graphics and Applications.

[8]  Amnon Shashua,et al.  The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  B. C. Heymans,et al.  A neural network for Opuntia leaf-form recognition , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

[10]  Zheru Chi,et al.  Combined thresholding and neural network approach for vein pattern extraction from leaf images , 2006 .

[11]  Maria Petrou,et al.  Image processing - the fundamentals , 1999 .

[12]  Xiaofeng Wang,et al.  Leaf shape based plant species recognition , 2007, Appl. Math. Comput..