DocumentCode :
237960
Title :
Non-destructive quality grading of mango (Mangifera Indica L) based on CIELab colour model and size
Author :
Pandey, Rashmi ; Gamit, Nikunj ; Naik, Sapan
Author_Institution :
Dept. of Comput. Eng., Uka Tarsadia Univ., Bardoli, India
fYear :
2014
fDate :
8-10 May 2014
Firstpage :
1246
Lastpage :
1251
Abstract :
In Gujarat, mango grading is done by using the human expert. Human expert grade the mangoes using hands and eyes which cause lack of objectivity, efficiency and accuracy. Automation plays a significant role to eliminate human´s interaction with the goal of achieving safety, accuracy and consistency. The aim of this paper is to achieve quality standard of mango using novel colour and size based grading algorithm. In this paper, Image database is prepared with different size and colour of mango which was collected from local vendors. CIELab colour model is used to classify mango in healthy and diseased category. Dominant density range based algorithm is applied to extract colour feature. After that Healthy mango is detected. Size feature is calculated using area and diameter in order to classify in different grade. At final stage, size feature is fed to fuzzy inference system for grading.
Keywords :
fuzzy reasoning; image colour analysis; occupational safety; production engineering computing; quality control; visual databases; CIELab colour model; Gujarat; Mangifera Indica L; fuzzy inference system; human expert; image database; mango; nondestructive quality grading; novel colour based grading algorithm; quality standard; safety; size based grading algorithm; Accuracy; Databases; Diseases; Feature extraction; Heating; Image segmentation; Standards; CIELab colour space; Classification; Fuzzy Inference system; Mango Grading; Size;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4799-3913-8
Type :
conf
DOI :
10.1109/ICACCCT.2014.7019298
Filename :
7019298
Link To Document :
بازگشت