Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Color Recognition Method Based on Improved Slic Superpixel Segmentation Algorithm

A technology of superpixel segmentation and color recognition, which is applied in the field of computer vision and image recognition, and can solve the problems of time-consuming and disadvantageous overall image analysis.

Active Publication Date: 2019-10-08
ANHUI CREARO TECH
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Traditional color image recognition technology usually judges the color of each pixel in the image based on the RGB color space, which is time-consuming and not conducive to the overall analysis of the image

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Color Recognition Method Based on Improved Slic Superpixel Segmentation Algorithm
  • A Color Recognition Method Based on Improved Slic Superpixel Segmentation Algorithm
  • A Color Recognition Method Based on Improved Slic Superpixel Segmentation Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] Such as figure 1 Shown is a flow chart based on SLIC color recognition, the method includes the following steps:

[0047] A color recognition method based on an improved SLIC superpixel segmentation algorithm, the steps are as follows:

[0048] (1) Load the Lab color mode sample set;

[0049] (2) Obtain the color image of the target to be identified and use the median filter to smooth the image and suppress noise, and then perform gamma correction on it to improve the contrast of the color image; thus avoiding a large number of tiny images after SLIC image segmentation area, the median filter can effectively preserve the boundary while smoothing the image and suppressing noise, such as figure 2 Shown is a schematic diagram of smoothing the image and suppressing noise on the 3×3 template using the median filter, from figure 2 It can be seen that if the pixel point is a noise point (larger pixel value), it is represented by the pixel point in the surrounding area, an...

Embodiment 2

[0078] Embodiment 2: Take the identification of blue color as an example to specifically illustrate its identification method:

[0079] (1) Load the Lab color mode sample set, the types of the color sample set include: black, red, yellow, blue, green, white and unknown;

[0080] (2) Obtain the color image of the target to be identified and use the median filter to smooth the image and suppress noise, and then perform gamma correction to improve the contrast of the color image;

[0081](3) Use the SLIC superpixel segmentation algorithm to perform superpixel segmentation processing on the preprocessed target color image, and segment the input picture into 500 different superpixel regions for an image of 612*563 size, and the number of iterations is 20 times;

[0082] (4) Carry out mean value processing to each superpixel region segmented through step (3), so that all pixel values ​​in each single superpixel region are the same;

[0083] (5) After processing in (4), the pixel va...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a color recognition method based on an improved SLIC superpixel segmentation algorithm, the steps of which are (1) loading a Lab color pattern sample set; (2) acquiring a target color image to be recognized and filtering the target color image , Correction preprocessing; (3) Process the preprocessed target color image with SLIC superpixel segmentation algorithm, and segment a plurality of different superpixel regions; (4) For each superpixel segmented by step (3), The pixel area is averaged so that all pixel values ​​in each single superpixel area are the same; (5) A pixel value in the superpixel area is compared with the color in the sample set loaded in step (1) using the Mahalanobis distance In comparison, the color corresponding to the minimum value of the Mahalanobis distance is the color of the superpixel region. This invention changes the traditional color recognition method of processing each pixel, greatly improving the processing speed and recognition accuracy.

Description

technical field [0001] The invention relates to the technical fields of computer vision and image recognition, in particular to a color recognition method based on an improved SLIC superpixel segmentation algorithm. Background technique [0002] Compared with grayscale images, color images have more information. The color recognition of color images is of great significance in real-time detection systems and automatic control. It has been widely used in modern production and scientific research, such as It has been widely used in remote sensing technology, industrial process control, material sorting and identification, image recognition and product quality inspection. [0003] The traditional color image recognition technology usually judges the color of each pixel in the image based on the RGB color space, which is time-consuming and not conducive to the overall analysis of the image. Since image colors are generally gradual, one color does not have only one pixel, so in ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/23213G06F18/23
Inventor 张芝华纪勇张传金姚莉莉谢宝万海峰
Owner ANHUI CREARO TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products