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Agriculture is the backbone to the living being thatplays a vital role to country’s economy. Agriculture productionis inversely affected by pest infestation and plant diseases. Plantsvitality is directly affected by the pests as poor or abnormal.Automatic pest detection and classification is an essential researchphenomenon, as early detection and classification of pests asthey appear on the plants may lead to minimizing the loss ofproduction. This study puts forth a comprehensive model thatwould facilitate the detection and classification of the pests byusing Artificial Neural Network (ANN). In this approach, theimage has been segmented from the fields by using enhancedK-Mean segmentation technique that identifies the pests or anyobject from the image. Subsequently, features will be extractedby using Discrete Cosine Transform (DCT) and classified usingANN to classify pests. The proposed approach is verified for fivepests that exhibited 94% effectiveness while classifying the pests.

K-means Based Automatic Pests Detection and Classification for Pesticides Spraying