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RBF neural network-based image watermark embedding and extraction method and device

A neural network algorithm and neural network technology, applied in the field of image watermarking, can solve the problems of poor robustness of embedded watermark images, and achieve the effects of good generalization ability, improved robustness, strong anti-noise ability and repair ability.

Inactive Publication Date: 2015-12-30
HENAN NORMAL UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to overcome the deficiencies in the prior art, and proposes an image watermark embedding and extraction method based on RBF neural network, and solves the problem of poor robustness for embedded watermark images through the optimized RBF neural network method. The present invention also proposes An image watermark embedding and extraction device based on RBF neural network

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  • RBF neural network-based image watermark embedding and extraction method and device
  • RBF neural network-based image watermark embedding and extraction method and device
  • RBF neural network-based image watermark embedding and extraction method and device

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Embodiment Construction

[0072] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0073] 1. Image watermark embedding and extraction method based on RBF neural network, the steps are as follows:

[0074] (1) Watermark image encryption

[0075] Scramble the original watermark image W with a size of 64×64, where W(i,j) is the pixel value of the original watermark image at position (i,j), that is, W={W(i,j),1≤ i≤64, 1≤j≤64}. The original watermark image is scrambled by affine transformation, and the encrypted watermark image is obtained by BP neural network algorithm according to the relationship between the original watermark image and the scrambled watermark image.

[0076] (1) Affine transformation

[0077] In this embodiment, an improved affine transformation formula is used to transform the original watermark image to obtain a scrambled image. The affine transformation expression is as follows:

[0078] When x

[...

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Abstract

The invention relates to an RBF neural network-based image watermark embedding and extraction method and device. According to the method, an original watermark image is encrypted, a carrier image is trained by using an optimized RBF neural network, and the encrypted watermark image is embedded into the original watermark image, wherein the optimal learning rate is set in an RBF neural network algorithm to realize self-adapting adjustment of a weight of the algorithm. The encrypted watermark image embedded in the carrier image is extracted through the optimized RBF neural network algorithm and a margin calculation, and the encrypted watermark image is subjected to recovery to obtain the original watermark image. The device comprises a scrambling module, an embedding module and an extraction module. Through the adoption of the method and the device, a contradiction between imperceptibility and robustness of the watermark image is balanced.

Description

technical field [0001] The invention relates to an image watermark embedding and extraction method and device based on RBF neural network, and relates to the technical field of image watermarking. Background technique [0002] Hiding image watermarks in digital image products is often used to prove the creator’s ownership of his works, or as a basis for identifying and prosecuting illegal infringement. Digital image watermarking has become an effective means of intellectual property protection and digital multimedia anti-counterfeiting. It has attracted people's attention and become a research hotspot. By scrambling and encrypting the watermark image and embedding it into the carrier image, transforming a meaningful digital image into a messy image and then transmitting it, the receiver decrypts the acquired image to restore Export carrier image and watermark image. In this way, some illegal personnel cannot obtain the original image information from the messy image during...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T1/00G06N3/08
Inventor 孙林李名常宝方王世勋赵永进郁丽萍王念念李源张非刘金金刘琛
Owner HENAN NORMAL UNIV
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