Browsing by Author "Shaikh, Mehvash Samir Fauziya (16DCO75)"

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    Fruit sorting and grading based on image processing
    (2020-05) Khan, Mubashir; Shaikh, Ashraf Tahir Parveen Bano (15CO35); Sayyed, Asim Farooque Najma (16DCO71); Shaikh, Mehvash Samir Fauziya (16DCO75)
    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.