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Today, considerable measure of Research is going ahead in recognition technique of iris images in imperfect environment. The proportion of securing flawed iris pictures in blemished environment is particularly high in light of off-pivot, posture variety, picture obscuring, enlightenment change, Noise and at a separation. In spite of the fact that there are numerous iris acknowledgment systems for...
Iris recognition is emerging as one of the important methods of biometrics-based identification systems. The biometric person authentication technique based on the pattern of the human iris is well suited to be applied to any access control system requiring a high level of security. Iris biometry has been proposed as a sound measure of personal identification. Segmentation places an important role...
In this paper, we present a novel approach for incorporating structural information into the hidden Markov modeling (HMM) framework for offline handwriting recognition. Traditionally, structural features have been used in recognition approaches that rely on accurate segmentation of words into smaller units (sub-words or characters). However, such segmentation based approaches do not perform well on...
Offline handwriting recognition of free-flowing Arabic text is a challenging task due to the plethora of factors that contribute to the variability in the data. In this paper, we address some of these sources of variability, and present experimental results on a large corpus of handwritten documents. Specific techniques such as the application of context-dependent Hidden Markov Models (HMMs) for the...
In this paper we present a robust multi-pass page segmentation algorithm. The first pass uses a modified smearing algorithm and the second pass performs a hybrid of bottom-up and top-down segmentation on the output of the first pass. Unlike traditional approaches, the bottom-up and top-down steps are based on primitive results of a smearing based page segmentation algorithm. Therefore, "split"...
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