Identification method based on textural features

A technology of texture features and recognition methods, applied in image data processing, instruments, calculations, etc., can solve problems such as blurred images, recognition errors, and image recognition systems that cannot recognize images, and achieve the effect of accurate texture features

Inactive Publication Date: 2020-10-27
方程式人工智能(安徽)有限公司
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0003] When the existing electronic smart products recognize the image, the image will be blurred or damaged, which will cause the image recognition system to fail to recognize the image, and the image will be directly transmitted to the image storage database for recognition, which is prone to recognition errors , cannot realize the accurate recognition of the image recognition system

Method used

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Embodiment Construction

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0021] The present invention proposes to comprise the following method steps:

[0022] S100: Segment the image to be processed by multiple preset segmentation methods, and obtain connection information between sub-images, wherein any sub-image obtained by each segmentation method is different from sub-images obtained by other segmentation methods ;

[0023] S200: Combine the sub-images obtained by segmenting according to the same segmentation method into a first combined image, and combine each of the first combined images into a s...

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Abstract

The invention discloses an identification method based on textural features. The invention belongs to the technical field of texture feature recognition. The method comprises the following steps: S100, segmenting a to-be-processed image through a plurality of preset segmentation modes, and obtaining the connection information between sub-images, any sub-image obtained in each segmentation mode being different from the sub-images obtained in other segmentation modes; S200, combining the sub-images obtained through segmentation in the same segmentation mode into first combined images, and combining all the first combined images into a second combined image; and S300, performing local orientation mode algorithm calculation on the second combined image to obtain regional texture features of each recognition region of the image. Compared with the prior art that texture features are extracted after the image to be processed is directly segmented, the method can accurately extract the texturefeatures of the image.

Description

technical field [0001] The invention relates to the technical field of texture feature recognition, in particular to a texture feature-based recognition method. Background technique [0002] Texture is a visual feature that reflects homogeneous phenomena in images, and it reflects the slow-changing or periodic-changing surface structure organization and arrangement properties of the object surface. Texture has three major signs: a certain local sequence repeats continuously, non-random arrangement, and roughly uniform unity in the texture area. Texture is different from image features such as grayscale and color. It is represented by the grayscale distribution of pixels and their surrounding spatial neighborhoods, that is, local texture information. Different degrees of repetition of local texture information, that is, global texture information. [0003] When the existing electronic smart products recognize the image, the image will be blurred or damaged, which will cause...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06T7/41
CPCG06T2207/10004G06T7/11G06T7/41
Inventor 陈红洲许健易宝方贤军
Owner 方程式人工智能(安徽)有限公司
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