Recognition of wheat varieties by image analysis

The objective of this paper is to develop a rapid, objective, and easy method for recognizing wheat varieties, which is important for breeding, milling and marketing. The method can be used in place of the existing procedures to remove subjectivity from wheat variety recognition. In contrast to previous work, most of which has focused on wheat morphological characteristics, the features utilized in this paper are based mainly on kernel color. Varietal classification is performed by using Support Vector Machines (SVMs) method. More than 96% correct recognition rates are achieved with bulk samples involving 16 varieties representing a wide range of wheat varieties, wheat class, and kernel types. The proportion of single wheat kernels correctly recognized ranges from 87% to 93%. The results were encouraging since the method proposed here can be easily conducted in routine inspection.