Abstract:
In recent years, automated machine vision based technology has become more
potential and important in many areas like Agricultural Sector and Food Processing
Industry. Grading and Sorting of the fruit is one of the most important process, but
this procedure is mostly carried out manually which is not efficient as it tends to
human error. An automatic fruit quality inspection system helps in speed up the
process improve accuracy and efficiency and reduce time.
In our project we have two main module, Grading Module and Sorting Module.
In Grading process, is carried out by capturing the fruit image using camera and this
image is interpreted using image processing various techniques.The Sorting process
is done by sorting the fruits based on Color. With the help of this two module we will
detect the defected fruits. We will be doing Size detection based on binary image of
fruits.
The Main aim of the our system is to Sort and Grade the variety of Fruits by using
different Image Processing Techniques and also by using Neural Networks(Sequential
Neural networks).Image Processing Techniques like converting color image to gray
scale image so with the help of thresholding we can get the amount of color the image
would be having like RGB color and canny edge detection for detecting the edge
of fruits and also neural network that can to changing input; so the network generates
the best possible result without needing to redesign the output criteria.with help of
this techniques we can make the the sorting and grading process more efficient than
the manual work.It will improve the quality as well as it will take less time.
Keywords: :Fruits, OpenCV, Contours,Image Processing, Edge Detection,Color
Detection, Canny Edge Detection, Neural Network,Camera.
