Botanical Leaf Disease Detection and Classification Using Convolutional Neural Network: A Hybrid Metaheuristic Enabled Approach

Computers

Sachin Kumar¹  Mikhail Zymbler¹  Pradeep Kumar Mallick²  Ami Kumar Parida³  Madhumini Mohapatra³ 

[1] Department of Computer Science, South Ural State University, Chelyabinsk 454080, Russia;School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIIT), Deemed to be University, Bhuvaneswar 751024, Odisha, India;School of Engineering and Technology (ECE), GIET University, Gunupur 765022, Odisha, India;

关键词: botanical leaf disease;    Black Widow Algorithm;    CNN;    Cat Swarm Optimization;   

DOI  :  10.3390/computers11050082

来源: DOAJ

【 摘 要 】

Botanical plants suffer from several types of diseases that must be identified early to improve the production of fruits and vegetables. Mango fruit is one of the most popular and desirable fruits worldwide due to its taste and richness in vitamins. However, plant diseases also affect these plants’ production and quality. This study proposes a convolutional neural network (CNN)-based metaheuristic approach for disease diagnosis and detection. The proposed approach involves preprocessing, image segmentation, feature extraction, and disease classification. First, the image of mango leaves is enhanced using histogram equalization and contrast enhancement. Then, a geometric mean-based neutrosophic with a fuzzy c-means method is used for segmentation. Next, the essential features are retrieved from the segmented images, including the Upgraded Local Binary Pattern (ULBP), color, and pixel features. Finally, these features are given into the disease detection phase, which is modeled using a Convolutional Neural Network (CNN) (deep learning model). Furthermore, to enhance the classification accuracy of CNN, the weights are fine-tuned using a new hybrid optimization model referred to as Cat Swarm Updated Black Widow Model (CSUBW). The new hybrid optimization model is developed by hybridizing the standard Cat Swarm Optimization Algorithm (CSO) and Black Widow Optimization Algorithm (BWO). Finally, a performance evaluation is undergone to validate the efficiency of the projected model.

【 授权许可】

Unknown