DocumentCode
3579098
Title
Apple fruit detection and counting using computer vision techniques
Author
Syal, Anisha ; Garg, Divya ; Sharma, Shanu
Author_Institution
CSE Department, ASET, Amity University, Noida, Uttar Pradesh, India
fYear
2014
Firstpage
1
Lastpage
6
Abstract
In agriculture sector the problem of identification and counting the number of fruits on trees plays an important role in crop estimation work. At present manual counting of fruits and vegetables is carried out at many places. Manual counting has many drawbacks as it is time consuming and requires plenty of labors. The automated fruit counting approach can help crop management system by providing valuable information for forecasting yields or by planning harvesting schedule to attain more productivity. This work presents an automated and efficient fruit counting system using computer vision techniques. The proposed system uses minimum Euclidean distance based segmentation technique for segmenting the fruit region from the input image. Further circle overlaying is done on the fruit region and in the last fruits are counted on the basis of the centroid of the fruit regions. This proposed system is correctly detecting and counting the apples on the test images
Keywords
Agriculture; Graphical user interfaces; Image color analysis; Image segmentation; Manuals; Testing; Training; Computer Vision; Euclidean distance; Fruit Localization; L∗a∗b Color space;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Computing Research (ICCIC), 2014 IEEE International Conference on
Print_ISBN
978-1-4799-3974-9
Type
conf
DOI
10.1109/ICCIC.2014.7238364
Filename
7238364
Link To Document