Intelligent classification method for colors of solid wood boards

A classification method and plate technology, applied in the field of image recognition, can solve the problems of high image feature dimension, false detection, unfavorable retrieval, etc., and achieve the effect of low feature vector dimension

Active Publication Date: 2021-06-22
NANJING FORESTRY UNIV
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AI Technical Summary

Problems solved by technology

Quantization processing can easily lead to false detection, and the generated image feature dimension is high, which is not conducive to retrieval

Method used

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  • Intelligent classification method for colors of solid wood boards
  • Intelligent classification method for colors of solid wood boards
  • Intelligent classification method for colors of solid wood boards

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Embodiment Construction

[0030] The specific embodiment of the present invention is described further below according to accompanying drawing:

[0031] An intelligent classification method for solid wood board color, such as figure 2 shown, including:

[0032] Step 1: Collect multiple pictures of solid wood panels, and preprocess the pictures of solid wood panels.

[0033] During the acquisition process of the solid wood panel image, the background information of the solid wood panel will also be stored in the picture, which will have a certain impact on the feature extraction of the solid wood panel image, so a series of preprocessing is performed on the solid wood panel image, including Image smoothing, image sharpening, image morphological operations, and image background removal for solid wood panels. The specific preprocessing process is as follows figure 1 shown.

[0034] Step 2: Transform each solid wood panel picture from RGB color space to Lab color space and HSV color space respectively...

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Abstract

The invention discloses an intelligent classification method for colors of solid wood boards. The method comprises the following steps: preprocessing solid wood board pictures; converting an RGB color space into a Lab color space and an HSV color space; obtaining a first moment and a second moment of colors of the Lab color space and the HSV color space; clustering the pictures by using a K-Means clustering algorithm; performing main color extraction on the solid wood board pictures after low-pass filtering by adopting a main color extraction method based on a K-Means clustering algorithm, and performing grade division according to the main color content; performing high-pass filtering on the pictures to obtain texture information, and dividing the pictures into straight grains or curved grains; labeling the solid wood board pictures, and making a sample set; and inputting the to-be-classified solid wood board pictures into an optimal color classification model obtained by training and verification to realize color classification of a solid wood board. According to the method, the colors of the solid wood board pictures can be effectively classified, the method does not need color space quantization, and the feature vector dimensionality is low.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to an intelligent color classification method for solid wood boards. Background technique [0002] Color moments are a simple and effective representation method of color features. There are first-order moments (mean, mean), second-order moments (variance, variance) and third-order moments (slope, skewness), etc. Since color information is mainly distributed in low-order Moments, so the first-order moment, second-order moment and third-order moment are sufficient to express the color distribution of the image, and the color moment has been proved to be effective in representing the color distribution in the image. [0003] Color is one of the most important contents of color images and is widely used in image retrieval. However, when extracting color features from an image, many algorithms must first quantify the image. Quantization processing is easy to caus...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/90G06K9/46G06K9/62G06N3/08G06N20/00
CPCG06T7/0004G06T7/90G06N20/00G06N3/088G06T2207/10024G06T2207/20081G06T2207/30161G06V10/56G06F18/23213G06F18/241
Inventor 刘英王争光丁奉龙杨雨图倪超庄子龙周海燕费叶琦唐敏缑斌丽
Owner NANJING FORESTRY UNIV
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