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

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.