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The perceptual image hash has been widely used for integrity check of digital image content. Existing image hashes fail to identify the origin of image acquisition and non-repudiable authentication is contingent on the privacy of secret key. This paper presents a new and more secure image hashing scheme by exploiting the CMOS image sensor physical unclonable function (PUF) as a root of trust to imprint...
In this paper, a novel learning methodology for face recognition, LearnIng From Testing data (LIFT) framework, is proposed. Considering many face recognition problems featured by the inadequate training examples and availability of the vast testing examples, we aim to explore the useful information from the testing data to facilitate learning. The one-against-all technique is integrated into the learning...
We propose a model for extracting facial features robustly for face recognition under large pose variations in videos. The facial features are retrieved via Gabor Wavelet Transform with an embedded Hidden Markov Model (HMM), which decodes each observed face image into a state sequence. While an HMM can segment images into features at a fixed pose, multiple HMMs are trained for each individual to extract...
This paper proposes a novel feature ranking method, DensityRank, based on kernel estimation on the feature spaces to improve the classification performance. As the availability of raw data in many of today's applications continues to grow at an explosive rate, it is critical to assess the learning capabilities of different features and select the important subset of features to improve learning accuracy...
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