Abstract: Arabic script character recognition remains a challenging task due to its cursive nature. The aim of feature extraction from the input strokes reduces the input pattern to avoid complexities while maintaining the high accuracy. Feature extraction in pattern recognition problems involves the extraction of unique and salient patterns from the preprocessed data in order to enhance the discriminatory power and reduce the data for classification and it is crucial for the success of recognition system. We proposed feature level fusion for Arabic character recognition. We extracted structural and directional features for handwritten stroke and fused these feature to form more discriminant feature matrix. The feature level fusion for handwritten character recognition provides considerable gain in accuracy. The fusion of feature is also suitable for other handwritten tasks i.e. personality determination, writer identification where the more variations are required

• Publication Date: 14-Jul-2012
• DOI: 10.15224/978-981-07-2969-1-123
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Abstract: Embodiments of this paper includes the study of steganography and digital watermarking as a technique of hiding images. Various algorithms on spatial and frequency domain transformation have been studied and their Signal-to-Noise Ratio has been computed. The processor complexity has also been checked to find out which algorithm can efficiently work on robust environment. The original image is decomposed in DWT domain in to three hierarchical levels and watermarks it with a logo image. The watermark is added to the DWT image according to a certain threshold. The watermark can be extracted at lower resolution without computational complexity. Wavelets play an important role in the upcoming compression standards such as JPEG2000. Experimentally it has been shown that a watermark signal can be embedded in high-pass wavelet coefficients without any impact on the image visual fidelity. Many transformations techniques are there but only a few have been studied and a simple comparison

• Publication Date: 03-Jun-2011
• DOI: 10.15224/978-981-07-1847-3-1027
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