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Generative Information Hiding of Iris Feature Data Based on Gaussian Fuzzy Algorithm

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Abstract The existing methods used for hiding the iris feature data were time-consuming for iris feature extraction. Meanwhile, the information security after hiding was also low, leading to low efficiency and security of information hiding. Therefore, a method of hiding iris features data generative information based on a Gaussian fuzzy algorithm was proposed. In the preprocessing stage of the image, the weighted average method was adopted for the gray-level transformation of the iris image, and the Gaussian fuzzy algorithm was used to smooth the image. In addition, the Laplacian convolution kernel was used to sharpen the image. The iris regions were normalized. The iris feature data was extracted by employing 2D Gabor wavelet. Moreover, the iris feature data was encrypted and decrypted using the AES algorithm, and hence, effectively enhancing the security of the generative information of iris feature data. Experimental results show that the proposed method can extract iris feature information within ten seconds, and the data security coefficient is high thus the proposed method efficiently realizes the information hiding.
Title: Generative Information Hiding of Iris Feature Data Based on Gaussian Fuzzy Algorithm
Description:
Abstract The existing methods used for hiding the iris feature data were time-consuming for iris feature extraction.
Meanwhile, the information security after hiding was also low, leading to low efficiency and security of information hiding.
Therefore, a method of hiding iris features data generative information based on a Gaussian fuzzy algorithm was proposed.
In the preprocessing stage of the image, the weighted average method was adopted for the gray-level transformation of the iris image, and the Gaussian fuzzy algorithm was used to smooth the image.
In addition, the Laplacian convolution kernel was used to sharpen the image.
The iris regions were normalized.
The iris feature data was extracted by employing 2D Gabor wavelet.
Moreover, the iris feature data was encrypted and decrypted using the AES algorithm, and hence, effectively enhancing the security of the generative information of iris feature data.
Experimental results show that the proposed method can extract iris feature information within ten seconds, and the data security coefficient is high thus the proposed method efficiently realizes the information hiding.

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