SAID SHEHATA

We propose a technique for effective extraction of bilingual phrases from word alignments using morphological processing. Morphological processing leads to an increase of the frequency of words in the corpus, consequently reduces Alignment Error Rate (AER). Intuitively, better word alignments enhance the quality of bilingual phrases extracted. Using alignments of a stemmed corpus for phrase extraction, instead of alignments of a raw one, shows significant improvements in translation quality, especially with small corpora.

This paper presents an efficient image registration technique using the Q-shift complex wavelet transform (Q-shift CWT). It is chosen for its key advantages compared to other wavelet transforms; such as shift invariance, directional selectivity, perfect reconstruction, limited redundancy and efficient computation. The experiments show that the proposed algorithm improves the computational efficiency and yields robust and consistent image registration compared with the classical wavelet transform.

The benefit of high radix Booth encoders in reducing the number of partial products in fast multipliers has been hampered by the complexity of generating the hard multiples. The use of redundant binary (RB) Booth encoder can overcome this problem and avoid the error compensation vector but at the cost of doubling the number of RB partial products. This paper presents a novel covalent RB Booth encoder to generate a compound RB partial product from two adjacent Booth encoded digits. The new encoder fully exploits the characteristics of Booth encoded numbers to restore the effective partial product reduction rate of RB Booth encoder while maintaining the simplicity of hard multiple generators and eliminating the constant correction vector. A legitimate comparison on an $8 \times 8$-bit RB multiplier prototype shows that the multiplier constructed with our proposed Booth encoder consumes lower power and computes faster than those with the normal binary and redundant binary Booth encoders.