Fingerprint segmentation is one of the most important preprocessing steps in an automatic fingerprint identification system (AFIS). It is used to separate a fingerprint area iforeground) from the image background. Accurate segmentation of a fingerprint will greatly reduce the computation time of the following processing steps, and discard many spurious minutiae. In this paper, a new segmentation algorithm is presented. Apart from its simplicity, it is characterized by being neither depend on empirical thresholds chosen by experts or a learned model trained by elements generated from manually segmented fingerprints. The algorithm uses the block range as a feature to achieve fingerprint segmentation. Then, some Morphological closing and opening operations are performed, to extract the foreground from the image.The performance of the proposed technique is checked by evaluating the classification error (Err). Experimental results have shown that when analyzing FVC2004, FVC2002, and FVC2000 databases using the proposed algorithm, the average classification error rates are much less than those obtained by other approaches. Several illustrative examples are given to verifY this conclusion.

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Zernike moments (ZM), are extensively used in pattern recognition and image classification. However, they suffer from severe computational errors especially as the moment order increases. In this paper, in order to reduce the effects of these errors and make ZM suitable for image processing applications, it is proposed to use Bspline interpolation to interpolate between image pixels. Due to the smooth and robust performance of Bspline interpolation, significant image quality improvements can be achieved. Having significantly improving the computations of ZM, the paper also proposes to use the rotation invariant feature of ZM, in developing a watermarking scheme that is insensitive to rotations or rotation attacks. In this respect, the Natural Preserving Watermarking technique known for its robustness to cropping, compression and noise attacks has been modified to be rotational invariant using the proposed ZM methods. Several simulation experiments are given to verify these results.

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infectious diseases [1]. Many species belonging to genera Anopheles, Aedes and Culex, are the mechanical and biological vectors for the pathogens of various diseases that affect both animals and humans [2][3][4][5][6]. Culicids have 44 genera and 3500 species with medical importance [7]. They play an important role in the transmission of parasites and pathogens of high public health concerns including malaria, dengue, filariasis, yellow fever, Japanese encephalitis, West Nile and Zika virus [8][9]. Control of these diseases