Identification of flower based on the intelligent system

computer engineering

Nowadays it is very important to identify naturally occurring objects and recognize their types. To identify different flower images based on its surface parameter is challenging and also an expensive task. Flower classification is a useful way for grouping a flower in certain class using specific features. Flowers have different parameters like color, texture and grains. The combined feature extracted from each of its parameter can be used to identify flower type and recognize its signature. Different supervised classification algorithms are being used to build model. Flower surface has different parameters like grain, color, texture etc. Image color is a combination of similar patterns with a regular frequency. It is an attribute that represents a spatial pixel arrangement in a region. Flower color contains clusters of grain patches with regular interval. So we can identify different flowers based on its color image. The feature extracted from color parameter is used to identify flower type or recognize its signature.

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