NDLI: Identification of fish species based on image processing and statistical analysis research

Content Provider	IEEE Xplore Digital Library
Author	Lian Li Jinqi Hong
Copyright Year	2014
Description	Author affiliation: Sch. of Electr. Eng., Tianjin Univ. of Technol., Tianjin, China (Lian Li; Jinqi Hong)
Abstract	For more fish varieties, to the subsequent processing and marketing, which is necessary to classify the types of fish. This study is based on image processing technology to classify the types of fish, four fish to make use of the existing image acquisition device for collecting samples, through the MATLAB software for image preprocessing, such as fish gray, binarization, image enhancement, contour extraction to extract the 11 feature parameters of four fish species, such as using the principal component analysis (PCA) to 11 characteristic parameters for dimension reduction, this study took four principal component. Then use SPSS software to establish fisher and mahalanobis distance model, the combination of four principal component reuse component to build a model to classify the four different kinds of fish. Through SPSS software simulation and identification results show that the average recognition rate of 96.67%, which can be well applied to the fish species identification technology.
Starting Page	1155
Ending Page	1160
File Size	465397
Page Count	6
File Format	PDF
ISBN	9781479939787
e-ISBN	9781479939794
DOI	10.1109/ICMA.2014.6885861
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Marine animals Feature extraction Image color analysis Principal component analysis Object recognition Software identification image processing principal components analysis fisher mahalanobis distance fish species
Content Type	Text
Resource Type	Article

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