Image character editing method of improved FANnet generative network

A character and editing technology, applied in the field of image recognition, can solve problems such as inability to ensure consistent image style, inability to implement image character editing work well, identify font structure or color characteristics of real-scene image characters, etc., to achieve improvement problems and limitations , Maintain visual smoothness, high visual smoothness effect

Active Publication Date: 2021-07-23
HENAN NORMAL UNIV
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AI Technical Summary

Problems solved by technology

Its main function is text recognition and extraction. For its editing function, it simply performs image text recognition and erasing and then replaces the modified text, which cannot be guaranteed to be consistent with the original image style.
In 2019, Wu Liang designed three networks: the foreground text migration network, the background erasing network, and the foreground and background fusion network to realize the real-scene image text editing work, but the errors that occur in each network...

Method used

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  • Image character editing method of improved FANnet generative network
  • Image character editing method of improved FANnet generative network
  • Image character editing method of improved FANnet generative network

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Embodiment Construction

[0029] The image character editing method of the improved FANnet generative network consists of the following steps: (1) select the source letter to be replaced from the image, and extract the source letter by the adaptive target detection model of the HC saliency detection algorithm and the custom threshold segmentation algorithm; Binary image; (2) generate target letter binary image through FANnet network; (3) use color complexity-based adaptive local color transfer model to perform color migration on the obtained target binary image and replace source letter with generated letter . In step (1), a custom detection area is used to determine the area that needs to be modified, and an adaptive target detection model is used to detect the bounding box of each letter in the area. For all letters in the determined area, you can select any source letter that you want to be modified, and specify the target letter that you want to replace. Based on these inputs, steps such as color ...

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Abstract

The invention provides an image character editing method of an improved FANnet generative network. The method comprises the following steps: firstly, accurately extracting image characters defined by a user by using an improved adaptive character segmentation model based on an HC saliency detection algorithm; secondly, generating a network according to the FANnet, and generating a target character binary image consistent with the font of the source character; and finally, migrating the color of the source character to the target character through the proposed local color migration model for color complexity discrimination. Therefore, the target editing and modifying character highly consistent with the font structure and color change of the source character is generated, and the purpose of character editing is achieved. Experimental results show that the method is superior to an existing algorithm. For actual scene image characters with relatively complex font structures and color gradient distribution, the invention is also very effective, and has certain theoretical significance and application prospects for image reutilization, automatic error correction of an image character computer, text information restorage and the like.

Description

technical field [0001] The invention belongs to the technical field of image recognition, in particular to an image character editing method for improving the FANnet generation network. Background technique [0002] In today's international society, English characters as an international common language appear in many public places; pinyin characters with the same geometric structure characteristics as English characters are also very important. When these characters appear in the image, especially when the image style is complex, it is difficult to directly edit and modify it. Font style transfer and text generation is an important research field of artificial intelligence. Whether it is a real picture or an electronic rendering, it always contains a lot of text information. These text information can help readers better understand the contextual semantics and scene information in the image. Unlike modifying and editing text in text, when a text in an image is wrong or n...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06K9/46G06N3/04G06N3/08
CPCG06N3/08G06V30/32G06V30/153G06V10/56G06V2201/07G06N3/045
Inventor 刘尚旺李名刘国奇袁培燕孙林
Owner HENAN NORMAL UNIV
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