Image sensors play a vital role in many image sensing and capture applications. Among the various types of image sensors, complementary metal oxide semiconductor (CMOS) based active pixel sensors (APS), which are characterized by reduced pixel size, give fast readouts and reduced noise. APS are used in many applications such as mobile cameras, digital cameras, Webcams, and many consumer, commercial and scientific applications. With these developments and applications, CMOS APS designs are challenging the old and mature technology of charged couple device (CCD) sensors. With the continuous improvements of APS architecture, pixel designs, along with the development of nanometer CMOS fabrications technologies, APS are optimized for optical sensing. In addition, APS offers very low-power and low-voltage operations and is suitable for monolithic integration, thus allowing manufacturers to integrate more functionality on the array and building low-cost camera-on-a-chip. In this thesis, I explore the current state-of-the-art of CMOS APS by examining various types of APS. I show design and simulation results of one of the most commonly used APS in consumer applications, i.e. photodiode based APS. We also present an approach for technology scaling of the devices in photodiode APS to present CMOS technologies. Finally, I present the most modern CMOS …

Power dissipation of integrated circuits is the most demanding issue for very large scale integration (VLSI) design engineers, especially for portable and mobile applications. Use of multiple supply voltages systems, which employs level converter between two voltage islands is one of the most effective ways to reduce power consumption. In this thesis work, a unique level converter known as universal level converter (ULC), capable of four distinct level converting operations, is proposed. The schematic and layout of ULC are built and simulated using CADENCE. The ULC is characterized by performing three analysis such as parametric, power, and load analysis which prove that the design has an average power consumption reduction of about 85-97% and capable of producing stable output at low voltages like 0.45V even under varying load conditions.

Elliptic curve cryptography (ECC) is an alternative to traditional techniques for public key cryptography. It offers smaller key size without sacrificing security level. Tate pairing is a bilinear map used in identity based cryptography schemes. In a typical elliptic curve cryptosystem, elliptic curve point multiplication is the most computationally expensive component. Similarly, Tate pairing is also quite computationally expensive. Therefore, it is more attractive to implement the ECC and Tate pairing using hardware than using software. The bases of both ECC and Tate pairing are Galois field arithmetic units. In this thesis, I propose the FPGA implementations of the elliptic curve point multiplication in GF (2283) as well as Tate pairing computation on supersingular elliptic curve in GF (2283). I have designed and synthesized the elliptic curve point multiplication and Tate pairing module using Xilinx's FPGA, as well as synthesized all the Galois arithmetic units used in the designs. Experimental results demonstrate that the FPGA implementation can speedup the elliptic curve point multiplication by 31.6 times compared to software based implementation. The results also demonstrate that the FPGA implementation can speedup the Tate pairing computation by 152 times compared to software based implementation.

Recently, there is a great interest in moving object tracking in the fields of security and surveillance. Object recognition under partial occlusion is the core of any object tracking system. This thesis presents an automatic and real-time color object-recognition system which is not only robust but also occlusion tolerant. The intended use of the system is to recognize and track external vehicles entered inside a secured area like a school campus or any army base. Statistical morphological skeleton is used to represent the visible shape of the vehicle. Simple curve matching and different feature based matching techniques are used to recognize the segmented vehicle. Features of the vehicle are extracted upon entering the secured area. The vehicle is recognized from either a digital video frame or a static digital image when needed. The recognition engine will help the design of a high performance tracking system meant for remote video surveillance.