Leaf Disease Detection using Image Processing

The revelation of plant disease is a prominent research theme in the field of computer science. With the aid of Intelligent systems, the diseases can be detected effectively .The plant leaves are mainly affected by varied micro organisms. This paper centers on the discovery of disease in plants using the input picture. The disease identification concerns the steps like transfiguration of the picture format from RGB to Grayscale. Adaptive Histogram Equalization (AHE) is accustomed to improvise the contrast in the picture. The 13 prominent attributes are extracted by handling a feature extraction method called GLCM or Gray Level Co-occurrence Matrix .The standard benchmark images are trained using SVM classifier and the outcomes are displayed in the output screen.

[1]  Anjali A. Yadav,et al.  SVM classifier based grape leaf disease detection , 2016, 2016 Conference on Advances in Signal Processing (CASP).

[2]  Karol Myszkowski,et al.  Apparent Greyscale: A Simple and Fast Conversion to Perceptually Accurate Images and Video , 2008, Comput. Graph. Forum.

[3]  Uday Pratap Singh,et al.  Multilayer Convolution Neural Network for the Classification of Mango Leaves Infected by Anthracnose Disease , 2019, IEEE Access.

[4]  P. Sathyanarayana,et al.  Image Texture Feature Extraction Using GLCM Approach , 2013 .

[5]  Miss. Dhanashree S. Kalel,et al.  Color, Shape and Texture feature extraction for Content Based Image Retrieval System: A Study , 2016 .

[6]  Myung-Ryul Choi,et al.  A contrast enhancement method using dynamic range separate histogram equalization , 2008, IEEE Transactions on Consumer Electronics.

[7]  Neil A. Dodgson,et al.  Decolorize: Fast, contrast enhancing, color to grayscale conversion , 2007, Pattern Recognit..

[8]  Monika Jhuria,et al.  Image processing for smart farming: Detection of disease and fruit grading , 2013, 2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013).

[9]  Rahul Das,et al.  Identification of plant leaf diseases using image processing techniques , 2017, 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR).

[10]  Khursheed Aurangzeb,et al.  An Optimized Method for Segmentation and Classification of Apple Diseases Based on Strong Correlation and Genetic Algorithm Based Feature Selection , 2019, IEEE Access.

[11]  S. Zhang,et al.  Plant disease recognition based on plant leaf image. , 2015 .

[12]  Zhiyuan Xu,et al.  Fog Removal from Video Sequences Using Contrast Limited Adaptive Histogram Equalization , 2009, 2009 International Conference on Computational Intelligence and Software Engineering.

[13]  P. Jaganathan,et al.  A new RBF kernel based learning method applied to multiclass dermatology diseases classification , 2013, 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES.