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FPGA Implementation of Point Processes using Xilinx System Generator.
Computers and Electronics in Agriculture, Vol.
Automatic Grading of Bi-Coloured Apples by Multispectral Machine Vision. International Association of Scientific Innovation and Research, Vol. Comparative Analysis of Feature Extraction Methods for Fruit Grading Classifications. Journal of Emerging Trends in Computing and Information Sciences, Vol. Fruit Recognition using Colour and Texture Features. International Journal of Research in Engineering and Technology, Vol. The Quality Identification of Fruits in Image Processing using MATLAB. Vision based Features in Moisture Content Measurement during Raisin Production. International journal on image and video processing, (ICTACT), Vol 9, Issue 02. Keywords: Fumigation, multithresh, Active contour, KNN, GLCM The K-NN classification is used to classify the sulphur added copra at different levels. The features are extracted from the image to differentiate normal and sulphur copra by using GLCM technique. The region of interest is segmented by using multithresh and active contour. The copra images are acquired with and without presence of sulphur. The idea is to identifying the presence of sulphur using image processing techniques and comparing with the real time estimation.
The Sulphur in excess can cause brain cell death, brain damage, blindness. The post-processing includes the fumigation of copra under sulphur. The copra is dried under open sunlight on the drying yard. The dried coconut meat is known as copra and it is a source of coconut oil, which is used in enormous quantities for making fats for baking and confectionery. There is 11.1 million of ton of coconut was cultivated. Over 70 % of the rural households depend on agriculture. Agriculture plays a vital role in Indian Economy.