Suitability of Feature Extraction Methods in Recognition and Classification of Grains, Fruits and Flowers

Abstract

This paper presents the suitability of feature extraction methods for the identification and classification of certain agriculture and horticulture crops. Primarily, agriculture/horticulture crops are recognized based on their shape, size, color, texture and the like. When crops exhibit different shapes and sizes, it is customary to choose the shape and size as the basic features. Certain crops are easily identified simply by color; for example, with crops like jowar, ground nut, pomegranate and mango, color becomes the discriminating feature. We have considered color as one of the features in this study. Some agriculture/horticulture crops have overlapping colors, such as wheat and ground nut or mango and orange. When we consider the bulk samples of such grains or fruits, the surface patterns vary from crop to crop. In such cases, the texture becomes ideal for recognition. Hence, we have obtained morphological features, like shape and size, color and textural features, of the image samples to recognize, classify and grade the agriculture/horticulture crops.