3 research outputs found
A novel parallel algorithm for surface editing and its FPGA implementation
A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySurface modelling and editing is one of important subjects in computer graphics. Decades of research in computer graphics has been carried out on both low-level, hardware-related algorithms and high-level, abstract software. Success of computer graphics has been seen in many application areas, such as multimedia, visualisation, virtual reality and the Internet. However, the hardware realisation of OpenGL architecture based on FPGA (field programmable gate array) is beyond the scope of most of computer graphics researches. It is an uncultivated research area where the OpenGL pipeline, from hardware through the whole embedded system (ES) up to applications, is implemented in an FPGA chip.
This research proposes a hybrid approach to investigating both software and hardware methods. It aims at bridging the gap between methods of software and hardware, and enhancing the overall performance for computer graphics. It consists of four parts, the construction of an FPGA-based ES, Mesa-OpenGL implementation for FPGA-based ESs, parallel processing, and a novel algorithm for surface modelling and editing.
The FPGA-based ES is built up. In addition to the Nios II soft processor and DDR SDRAM memory, it consists of the LCD display device, frame buffers, video pipeline, and algorithm-specified module to support the graphics processing.
Since there is no implementation of OpenGL ES available for FPGA-based ESs, a specific OpenGL implementation based on Mesa is carried out. Because of the limited FPGA resources, the implementation adopts the fixed-point arithmetic, which can offer faster computing and lower storage than the floating point arithmetic, and the accuracy satisfying the needs of 3D rendering. Moreover, the implementation includes BĂ©zier-spline curve and surface algorithms to support surface modelling and editing.
The pipelined parallelism and co-processors are used to accelerate graphics processing in this research. These two parallelism methods extend the traditional computation parallelism in fine-grained parallel tasks in the FPGA-base ESs.
The novel algorithm for surface modelling and editing, called Progressive and Mixing Algorithm (PAMA), is proposed and implemented on FPGA-based ES’s. Compared with two main surface editing methods, subdivision and deformation, the PAMA can eliminate the large storage requirement and computing cost of intermediated processes. With four independent shape parameters, the PAMA can be used to model and edit freely the shape of an open or closed surface that keeps globally the zero-order geometric continuity. The PAMA can be applied independently not only FPGA-based ESs but also other platforms.
With the parallel processing, small size, and low costs of computing, storage and power, the FPGA-based ES provides an effective hybrid solution to surface modelling and editing
Image Understanding for Automatic Human and Machine Separation.
PhDThe research presented in this thesis aims to extend the capabilities of human
interaction proofs in order to improve security in web applications and services.
The research focuses on developing a more robust and efficient Completely
Automated Public Turing test to tell Computers and Human Apart
(CAPTCHA) to increase the gap between human recognition and machine
recognition. Two main novel approaches are presented, each one of them targeting
a different area of human and machine recognition: a character recognition
test, and an image recognition test. Along with the novel approaches,
a categorisation for the available CAPTCHA methods is also introduced.
The character recognition CAPTCHA is based on the creation of depth
perception by using shadows to represent characters. The characters are created
by the imaginary shadows produced by a light source, using as a basis the
gestalt principle that human beings can perceive whole forms instead of just
a collection of simple lines and curves. This approach was developed in two
stages: firstly, two dimensional characters, and secondly three-dimensional
character models.
The image recognition CAPTCHA is based on the creation of cartoons
out of faces. The faces used belong to people in the entertainment business,
politicians, and sportsmen. The principal basis of this approach is that face
perception is a cognitive process that humans perform easily and with a high
rate of success. The process involves the use of face morphing techniques to
distort the faces into cartoons, allowing the resulting image to be more robust
against machine recognition.
Exhaustive tests on both approaches using OCR software, SIFT image
recognition, and face recognition software show an improvement in human
recognition rate, whilst preventing robots break through the tests