Abstract
This paper presents an image hashing technique for content verification using Discrete Wavelet Transform (DWT) approximation features. The proposed technique converts resized RGB color images to L * a * b * color images. Further, images are regularized using Gaussian low pass filter. A level 2, 2D DWT is applied on L * component of L * a * b * color image and the LL 2 approximation sub-band image is chosen for feature extraction. The features are extracted by utilizing a sequence of circles on approximation sub-band image. Finally, the robust binary hash is generated from extracted features. The experimental results indicate that the hash of the presented technique is invariant to standard content preserving manipulations and malicious content altering operations. The experiment results of Receiver Operating Characteristics (ROC) plots indicate that the presented technique shows strong discriminative and robustness capabilities. Besides, the hash of the proposed technique is shorter in length and key dependent.
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Vadlamudi, L.N., Vaddella, R.P.V., Devara, V. (2017). Robust Image Hashing Technique for Content Authentication based on DWT. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-10-2104-6_17
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DOI: https://doi.org/10.1007/978-981-10-2104-6_17
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