Classification of color objects like fruits using probability density function (PDF)

Fruits like apples are valued based on their appearance (i.e. color, sizes, shapes, presence of surface defects) and hence classified into different grades. Grading process helps in achieving better standards and quality of fruits. Of the many available color models, HSI model provides a highly effective color evaluation particularly for analyzing biological products. Human assessment furnishes only qualitative data and such inspection is time consuming and cost-intensive. Machine vision systems with specialized image processing software provide a solution that may satisfy the demand. The analysis was carried out on images of 187 apple fruits, shows that classification done based on median of PDF. In order to avoid the mismatch in grading the same it has been classified further using Histogram Intersection, which determines the closeness between two images i.e. 1 if two images are similar and 0 if they are dissimilar.