Wool cashmere recognition algorithm based on Gabor wavelet analysis

A wool and cashmere recognition algorithm technology, applied in the field of wool and cashmere recognition, can solve the problems of high subjectivity, time-consuming and labor-intensive, poor measurement consistency, etc., and achieves strong applicability, high accuracy of recognition results, high recognition rate high effect

Active Publication Date: 2016-06-15
TIANFANG TIANJIN STANDARD TESTING TECH CO LTD +1
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Problems solved by technology

By observing the scale shape and texture details of wool and cashmere under the microscope, the inspectors qualitatively classify the components of

Method used

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  • Wool cashmere recognition algorithm based on Gabor wavelet analysis
  • Wool cashmere recognition algorithm based on Gabor wavelet analysis
  • Wool cashmere recognition algorithm based on Gabor wavelet analysis

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Embodiment

[0029] The present invention includes online identification process and model learning process:

[0030] The on-line identification process is to perform qualitative analysis on the fiber images collected in real time, including the following steps:

[0031] (1) Image acquisition, using 3 million pixel industrial-grade ccd with Olympus CX41 biological microscope to capture images of cashmere wool fibers;

[0032] (2) Preprocessing: a Gaussian filter is used to smooth and filter the image to remove noise in the image. The Gaussian filter is a low-pass filter, and its process can be formally expressed as an input image I(x, y) Convolution with Gaussian kernel function G(x, y):

[0033] S(x,y)=I(x,y)×G(x,y;σ) where

[0034] b Adjust the gray level of the image to achieve image enhancement, set the data x ij Is the i row j column element in the image X, max x , min x are the maximum and minimum values ​​in X, respectively; x i ...

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Abstract

The invention discloses a wool cashmere recognition algorithm based on Gabor wavelet analysis, and the algorithm comprises an online recognition flow and a model learning flow. The online recognition flow comprises the following steps: (1), taking an image of wool cashmere fibers (2), carrying out the smooth filtering of the image through employing a Gaussian filter, and achieving the image enhancement through the gray scale adjustment of the image; (3), extracting an image target through employing the edge detection and contour extraction based on canny; (4), extracting Gabor characteristics; (5), calculating a result. The model learning model comprises the following steps: (1), accumulating a large amount of wool cashmere data in a database; (2), determining the class of a target fiber and the position of the target fiber through manual marking; (3), carrying out the preprocessing and feature extraction of the fiber image in the database, wherein the step (3) is consistent with the steps (2) and (4) in the online recognition flow; (4), employing a two-class SVM classifier in a learning process. The method can achieve a high recognition rate, is quick in recognition speed, is high in accuracy of the recognition result, and is high in applicability.

Description

technical field [0001] The invention belongs to the technical field of wool and cashmere recognition, in particular to a wool and cashmere recognition algorithm based on Gabor wavelet analysis. Background technique [0002] Cashmere fibers are slender, uniform and soft, and the textiles made of them are soft, smooth and warm, and are the first choice for high-end clothing. Due to its scarce output and high price, manufacturers often use different proportions of cashmere wool for blending. Both wool and cashmere are natural protein fibers, and their structures and shapes are very similar. It is very difficult to accurately judge the fiber type. [0003] The most commonly used fiber identification method is microscope observation. By observing the scale shape and texture details of wool and cashmere under the microscope, the inspectors qualitatively classify the components of cashmere wool according to their personal experience. This method is not only time-consuming and lab...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/60G06K9/46
CPCG06V10/44G06V10/20G06F18/2411
Inventor 单学蕾俞浩谢自力葛传兵魏俊玲孙学艳李一晗
Owner TIANFANG TIANJIN STANDARD TESTING TECH CO LTD
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