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 :
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