Defect Recognition of Fruit using Statistical Approach
Chetana.K.Shetty, S.B.Kulkarni, U.P.Kulkarni, Ramesh.K, Ravindra.Hegadi"Defect Recognition of Fruit using Statistical Approach", International Journal of Engineering Trends and Technology (IJETT), V22(7),331-334 April 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
An automated fruit defect recognition and a review of previous defect detection methods are reported. To identify the defects in various digital images visual inspection systems are used. Visual inspection systems have a scanned copy of an object to find the flaws in the object. The visual inspection systems are used in fruit defect detection, textile fabric defect detection, metal crack detection etc. In this work defect detection algorithm focuses on the cropped image (excluding background) of standard size 200*200. The images should be captured with proper focus. The region of the image is equally divided and computing the mean value of each region. Calculating the minimum mean, maximum mean, difference (minimum mean, maximum mean) and average (minimum mean, maximum mean). If the difference is greater than average then it is defected. This methodology is able to recognize fruit defects in natural conditions.
 K N Sivabalan and DR.D GNANADURAI, "Efficient defect detection algorithm for gray level digital images using gabor wavelet filter and gaussian filter," International Journal of Engineering Science and Technology (IJEST).
 Mohana S H, Prabhakar C J, and Praveen kumar P U, "Surface defect detection and grading of apples," Proc. of Int. Conf. on Multimedia Processing, Communication & Info. Tech, MPCIT.
 A Ertuzun, A Ercil, and A Serdaroglu, "Defect detection in textile fabric images using wavelet transforms and independent component analysis," vol. 16, No 1.
 H Alimohamdi and H Ahmady, "Detecting skin defect of fruits using optimal Gabor wavelet filter," 2006.
 M Ghazini, A Monadjemi, and K Jamshidi, "Defect detection of tiles using 2D Wavelet transform and statistical features," World Academy of Science, Engineering & Technology, 2009.
 Shao-ping Chen, Jia-ni Liao, and Gui-mei Zhang, "Otsu Image Segmentation Algorithm Based on Morphology and Wavelet Transformation.," in ICCRD, 2011.
 Rashmi Mishra and Ms. Dolly Shukla, "A Survey on Various Defect Detection," International Journal of Engineering Trends and Technology (IJETT), vol. 10, Apr 2014.
 Jaspinder Pal Singh, "Designing an FPGA Synthesizable Computer Vision Algorithm to Detect the Greening of Potatoes," International Journal of Engineering Trends and Technology (IJETT), vol. 8, Feb 2014.
Min_mean, Max_mean, Diff (Min_mean, Max_mean), Avg (Min_mean, Max_mean)