International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
IMAGE PROCESSING ALGORITHM FOR FRUIT IDENTIFICATION Pradeepkumar Choudhary1, Rahul Khandekar2, Aakash Borkar3 , Punit Chotaliya4 1,2,3,4 Student,
Dept. of Electronics and Telecommunication Engineering, K. J. Somaiya Institute of Engineering and Information Technology, Maharashtra, Mumbai. ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Fruits should be quickly and correctly
II.
differentiated from their surroundings for the fruit harvesting robot. Edge based and color based detection methods are generally used to segment images of fruits obtained under natural lighting conditions. In this work, Digitized images of mango fruits along with its background were selected from the Internet in order to find a mango in each image and to locate its exact position. We compared the results of Edge based and colored based segmentation results and found that color based segmentation outperforms the edge based segmentation in all aspects. The comparison results are shown in the segmented image results. Accordingly, a new mango detection method is proposed to position the centroid of mangoes.
DETECTION OF MANGO FRUIT ON TREE: A. Color based segmentation
KeyWords: color based segmentation, edge based segmentation, machine vision, clustering, OpenCV.
I.
INTRODUCTION
In the last decades, researchers have interested in fruit detection algorithms and applied many different computer vision techniques. The overall aim of most of these studies is robotic fruit harvesting [1]. But fresh fruit harvesting is a sensitive operation. According to [2], cost of harvesting by labors is very expensive and time consuming. In addition, picking of fruits by hand is very tedious. To solve these problems, human works can be replaced by automatic robots. Automatic harvesting operations reduce the harvesting costs [3]. For automatic fruit/vegetable harvesting systems, it is extremely important to effectively detect the object in outdoor conditions. There are several problems on fruit detection in outdoor condition, which can be classified into two groups: lighting and occlusion. Overcoming these problems is very crucial for the success of robotic harvesting. The first major task of a harvesting robot is to recognize and localize the fruit on the tree. This paper focuses on recognition of mango fruits by using edge and color based segmentation methods and we compare the results of both segmentation results. In the next section the details of our proposed edge and color based segmentation methods are presented. The results and discussion is given in section III. Finally, in section IV, conclusions of the proposed approach were presented.
Š 2017, IRJET
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Proposed Model: Pre-processing input images: In this step, we perform some necessary operators on the captured image. The captured image of size m*n is converted into square image of size 256*256 fig (a).
Image segmentation clustering Algorithm:
using
K-means
The image segmentation means that the original image is divided into desired number of parts. Its purpose is to cluster the pixels which have the same features in image. It is the first step of process. There are several methods for this aim. Some of the works are based on the histogram or clustering. In detection of fruit, it is purposed to separate
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