Investigating coastal oceanic environment is of great interest in pollution monitoring, tactical surveillance applications, exploration of natural undersea resources and predicting wave tides. Deployment of underwater sensor networks for real time investigation is the major challenge. Acoustic communication intends to be an open solution for continuous wireless sensor network in underwater scenarios.In this paper large-scale underwater Sensor Networks (UWSN) and Underwater Ad-hoc Networks (UANETs) to explore the oceanic environment is proposed. A kong wobbler carrying base station with acoustic communication devices is considered, which locates the pre-deployed underwater sensor modules through acoustic communication. The sensor modules are installed with various sensors and video capturing devices to study the underwater resources as well as for surveillance needs for predicting the environmental conditions. The simulation results are encouraging as this approach is extremely helpful in surveillance as the intruders are tracked and real-time video streaming is done.

Palmprint identification is the measurement of The palmprint line features include principal lines, wrinkles palmprint features for recognizing the identity of a user. and ridges. Ridges are the fine lines of the palmprint. It Palmprint is universal, easy to capture and does not change requires high-resolution image or inked palmprint image to much across time. Palmprint biometric system does not requires obtain its features. Wrinkles are the coarse line of the specialized acquisition devices. It is user-friendly and more . . acceptable by the public. Besides that, palmprint contains palmprntmwhile the prle aheajor line ati different types of features, such as geometry features, line available on most of the palm (headline, lifeline and features, point features, statistical features and texture features. heartline). The separation of wrinkles and principle lines are In this work, peg-less right hand images for 100 different difficult since some wrinkles might be as thick as principle individuals were acquired ten times. No special lighting is used lines [2]. in this setup. The hand image is segmented and its key points are Palmprint point features use the minutiae points or delta located. The hand image is aligned and cropped according to the points to identify an individual. Point features require highkey points. The palmprint image is enhanced and resized. resolution hand image [3] because low-resolution hand image Sequential modified Haar transform [1] is applied to the resized does not have a clear points location. Palmprint statistical

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