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A multi-exposure-based workpiece character image local detail enhancement fusion method

A character image and fusion method technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as poor lighting conditions in the production environment, and the impact of recognition and extraction information

Pending Publication Date: 2021-05-18
ZHEJIANG SCI-TECH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The poor lighting conditions of the production environment and the complex surface of the workpiece itself have a great impact on the recognition and extraction of information in the collected images

Method used

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  • A multi-exposure-based workpiece character image local detail enhancement fusion method
  • A multi-exposure-based workpiece character image local detail enhancement fusion method
  • A multi-exposure-based workpiece character image local detail enhancement fusion method

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Embodiment Construction

[0056] Please refer to the attached figure 1 Shown, the present invention is a kind of workpiece character image local detail enhancement fusion method based on multi-exposure, and it comprises following process steps:

[0057] 1) Constructing the source image weight item: This algorithm calculates the weight item of each source image by combining three quality indicators of pixel-level contrast, brightness and saturation, extracts the local details of the image, and constructs the initial weight map of the source image sequence.

[0058] By constructing three weight items of local contrast, brightness and saturation of the source image, the local details of the image are extracted to solve the problem that the local details of the source image are not obvious due to underexposure or overexposure. Specifically, let I i , i=1, 2, ..., N represents the color source image, convert the color source image to grayscale source image The conversion formula is as follows:

[0059] ...

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PUM

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Abstract

The invention relates to a multi-exposure-based workpiece character image local detail enhancement fusion method. The method comprises the following steps: (1) constructing a source image weight item; (2) refining the initial weight map; (3) carrying out Laplace reconstruction fusion; (4) extracting detail features of the exposure image; and (5) carrying out local detail enhancement fusion. According to the invention, the problems of unoptimistic situations such as overexposure or insufficient exposure of the workpiece character image, low local contrast ratio, serious color distortion and large amount of invisible local detail information can be well solved, and the high-quality local detail enhanced fusion image is obtained through fusion so as to help to effectively identify and extract information from the workpiece character image.

Description

【Technical field】 [0001] The invention relates to an image fusion method, in particular to a multi-exposure-based local detail enhancement fusion method of a workpiece character image, belonging to the technical field of digital image processing. 【Background technique】 [0002] With the continuous development of science and technology, the use of smart devices in life and production is becoming more and more popular. With the advantages of rich information and vivid and intuitive images, images have gradually become an important carrier for recording and transmitting information. Optical character recognition (OCR) is a kind of text that converts the image of handwritten or printed text into machine-coded text mechanically or electronically. As a form of data entry, it is widely used in practical applications. Common scenarios include document recognition, Invoice recognition, business card recognition, license plate recognition, etc.; in production, it is often used for li...

Claims

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Application Information

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IPC IPC(8): G06T5/50G06T5/00G06K9/20G06K9/46
CPCG06T5/50G06T2207/10004G06T2207/20016G06T2207/20221G06V10/22G06V10/44G06V10/462G06T5/94Y02P90/30
Inventor 向忠吴华雄周鼎钱淼胡旭东马淼
Owner ZHEJIANG SCI-TECH UNIV
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