  This paper presents a novel method to grade the date fruits based on the
combination of shape and texture features. The method begins with reducing the
specular reflection and small noise using a bilateral filter. Threshold based
segmentation is performed for background removal and fruit part selection from
the given image. Shape features is extracted using the contour of the date
fruit and texture features are extracted using Curvelet transform and Local
Binary Pattern (LBP) from the selected date fruit region. Finally, combinations
of shape and texture features are fused to grade the dates into six grades.
k-Nearest Neighbour(k-NN) classifier yields the best grading rate compared to
other two classifiers such as Support Vector Machine (SVM) and Linear
Discriminant(LDA) classifiers. The experiment result shows that our technique
achieves highest accuracy.
