NDLI: Detection Level of Raisins Based on Neural Network and Digital Image

Content Provider	IEEE Xplore Digital Library
Author	Li Xiaoling Liu Xiaoying
Copyright Year	2011
Abstract	In view of the draw backs of raisins grade identification in China, which still relies on photoelectric sorting and manual separation, ths paper presents a processing method on the basis of the technology of computer vision and digital image.Utilizing image processing technology, the researcher calculated the length of the long-short-axis, marked the location of it and calculated the 7 parameters, chroma, length, width and etc, 4 of which are chosen as the key characteristics of the BP input of network to build a network and identify the level of raisins through analysis of the external characteristics of raisins. The method is based on traditional characteristics detection, using boundary tracking algorithm and the length of the new long-short-axis detection algorithm. The result of experiment indicates that the calculating method and judging of the level of raisins are precise and accurate, with an average recognition rate of 92%. Therefore, the method has a great practical value, which can be applied to other agricultural products classification.
Starting Page	1
Ending Page	3
File Size	277378
Page Count	3
File Format	PDF
ISBN	9781457708558
e-ISBN	9781457708565
DOI	10.1109/PACCS.2011.5990209
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computer vision Image color analysis Manuals Feature extraction Sorting
Content Type	Text
Resource Type	Article

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