Survey: Crop Classification using Transform Domain Technique

Crops are highly cultivating all around the world and vary depending upon the quality of the land in each country. Crop classification is necessary to tell what crops they are and if they are good for that specific area. This classification will help agronomists to decide crop pattern and cultivation practice. Plants are a major source of food stuff, medicine and industry. However it is an important and difficult task to recognize species of crop on earth. Therefore it is necessary to design an appropriate recognition system of crops. Textures play important roles in crop classification applications, since images of real objects often do not exhibit regions of uniform and smooth intensities, but variations of intensities with certain repeated structures or patterns, referred to as visual texture. The textural patterns or structures mainly result from the physical surface properties, such as roughness or oriented structured of a tactile quality. It is widely recognized that a visual texture, which can easily perceive, is very difficult to define. The development in multi-resolution analysis such as DCT and wavelet transform help to overcome this difficulty. In this method, first of all, we created satellite imagery database of different crops and then extract features from each crop images and then different classifier are used for classification.