Vision chips have many applications in tracking systems, object recognition, image segmentation, etc. The advancement of CMOS technology and reduction of transistors sizes, have made many progress in improving of image quality, reduction of area and power consumption and increasing of computational speed. By using this technology and employing high density circuits, photo sensors and processing units are integrated in one chip. Elimination of the need for data transmission between the sensors and the off-chip circuits reduces power consumption and increases the processing speed. Vision chips based on their usage are designed in five different architectures. These architectures are different in terms of computational speed, power consumption and chip area. Block-based vision-chip is one of these architectures that consists of some similar circuit blocks, that each contains a group of photo pixels (e.g. a 16*16 array pixels) and one processor that works in parallel with other block processors. The main advantage of block based architecture is its scalability in terms of resolution and image size. In this work, this architecture is implemented on FPGA by using VHDL codes, and MRI images are processed in this structure. Basic reference information is obtained by using normal MRI images and fuzzy clustering. This information is used to process MRI images of patients with Alzheimer’s disease. In addition, an algorithm is introduced to find each block distance from the center part of the brain. By combining the result of the intensity fuzzy clustering algorithm with the spatial information of pixel, lesion and its location are detected in patient MRI images. A fixed point ALU is implemented and used in each block for fuzzy clustering computations. The implemented ALU has an accuracy of three decimal places. The proper size of the blocks is obtained, and based on that the clustering algorithm is implemented on FPGA. Comparing the results with the software results confirms the correct implementation of the algorithm. Key Words : Vision Chip, Pixel Array, Block Based Architecture, MRI Images, Fuzzy Clustering, Alzheimer’s Disease.
