MSC-CFS-ICA-based apple slight damage hyperspectral detection method

A MSC-CFS-ICA, slight damage technology, applied in the direction of color/spectral characteristic measurement, optical test defect/defect, measurement device, etc., can solve problems such as difficult detection, achieve image noise reduction, effective and accurate identification Effect

Inactive Publication Date: 2019-01-22
JIANGNAN UNIV
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Problems solved by technology

However, the characteristics of healthy and damaged areas are very similar in the visible range (400-700nm), so when the oxidative browning after fruit damage is limited, it is often difficult to detect

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  • MSC-CFS-ICA-based apple slight damage hyperspectral detection method

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and implement it, but the examples given are not intended to limit the present invention.

[0034] Most scholars detect fruit defects based on hyperspectral imaging technology combined with chemometric methods, but the commonly used feature band extraction algorithm usually extracts a large number of feature bands, the data redundancy is large, and the data processing is still cumbersome, which is not conducive to fruit quality. online detection. In addition, most studies did not take into account the impact of slight fruit damage over time, which does not conform to the actual situation of fruit quality detection. Therefore, the detection accuracy of fruit samples with different time damage needs further analysis.

[0035] A hyperspectral detection method for slight app...

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Abstract

The invention discloses an MSC-CFS-ICA-based apple slight damage hyperspectral detection method. The MSC-CFS-ICA-based apple slight damage hyperspectral detection method comprises the following stepsof acquiring an original hyperspectral image of an apple sample; extracting average spectral reflectivity data of the original hyperspectral image; preprocessing the average spectral reflectivity of an original hyperspectrum by using a multiplicative scatter correction algorithm; for the preprocessed spectral data, adopting a feature selection algorithm based on correlation, and selecting out a characteristic wavelength with high correlation with apple damage classification; and based on the characteristic wavelength, performing conversion by using independent component analysis to obtain a damage image, and obtaining a damage area through an adaptive threshold segmentation algorithm, so that the detection of apple damage is completed. The method has the beneficial effects that an AmericanSOC710VP hyperspectral imager is used for collecting hyperspectral images of Fuji apples with the waveband range of 400-1,000 nm (128 wave bands in total) in normal and different damage time.

Description

technical field [0001] The invention relates to the application technical field of applying hyperspectral technology to non-destructive detection of agricultural products, in particular to a hyperspectral detection method for slightly damaged apples based on MSC-CFS-ICA. Background technique [0002] Apple is the largest fruit in our country and one of the advantageous agricultural products in our country. Apples are easily damaged due to collision and extrusion during picking and transportation. The damage usually occurs under the peel, and the change in the appearance of the fruit is not obvious at the initial stage of damage, which is difficult to identify with the naked eye. The damaged tissue will brown within a few hours, and then cause the softening or water loss of the tissue, and finally lead to microbial infection and decay, affecting the quality. At present, most of the detection of diseases in the process of fruit collection is manual sorting and machine vision...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/25G01N21/88G06T7/00
CPCG01N21/25G01N21/8851G01N2021/8887G06T7/0002G06T2207/20104G06T2207/30128
Inventor 李光辉张萌
Owner JIANGNAN UNIV
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