In this paper the formal or static approach is presented in a context that encourages its integration into HDL-based courses at the senior or first year graduate level. In addition to the reliability factor, these techniques are proven to be cost effective since they help in reducing time allocated for test bench creation which is typically a time consuming and error prone activity. Recently, formal verification techniques have gained large attention and are becoming a key component in reducing the verification effort required to meet compressed design cycle times. This fact has tempted the scientific community to propose alternatives to the classical simulation. According to published work, verification of these ASICs has emerged as a major bottleneck consuming up to three-quarters of total pre-silicon resources. The rapid progress of chip fabrication technology has paved the way to the design of complex ASICs containing several million transistors. The implementation can be included in the video systems for live 3-D television applications and can be used as an independent hardware module in low-power integrated applications. The system performs with high efficiency and stability by using a full pipeline design, multiresolution processing, synchronizers which avoid clock domain crossing problems, efficient memory management, etc. The proposed field-programmable gate array-based architecture implements a fusion strategy matching algorithm for efficiency design. This paper presents a hardware implementation of a full high-definition (HD) depth estimation system that is capable of processing full HD resolution images with a maximum processing speed of 125 fps and a disparity search range of 240 pixels. Meanwhile, high-resolution depth maps are necessary to provide a good image quality on autostereoscopic displays which deliver stereo content without the need for 3-D glasses. The depth estimation algorithm is especially complex and it is an obstacle for real-time system implementation. Three-dimensional (3-D) video brings people strong visual perspective experience, but also introduces large data and complexity processing problems.
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