Theses and Dissertations

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    ItemOpen Access
    Road detection for intelligent transport systems
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2015) Shah, Falak; Shah, Pratik; Dubey, Rahul
    Road detection is an important machine vision problem with applications to driver assistance systems and autonomous vehicles. We carried out a literature survey of the state of the art road detection algorithms. Simulations of these algorithms were performed on road images taken from multiple datasets which revealed certain limitations such as failure under shadows or in the absence of lane markers. This is why the past few years saw the emergence of illuminant invariant based road detection techniques as the state of the art. As the name suggests, illuminant invariant is a feature which contains the colour information of the surface being captured independent of the illumination source. However, the derivation of illuminant invariant image from the RGB image makes use of the assumption that the surface being captured is lambertian. The smooth road surfaces that reflect sunlight are specular and they violate the lambertian assumption. Thus, the algorithms based on illuminant invariant feature fail to detect the road region containing specularities. The road detection algorithm functions by building a road model in the illuminant invariant feature space for each frame. The white markings that are painted over the roads in the form of zebra crossings, lane markers and arrows are not included into the road model. Hence, the algorithm fails to detect them as a part of road region. The first contribution of this thesis is to address the limitations of specularities and lane markers, thus improving the robustness of the state of the art road detection algorithm. We propose a novel specularity detection and removal method for road scenes which also removes the white markings present in the road image. The region of the image containing specularities/ markers is filled with same shade as its surrounding region. Any road detection algorithm has two aspects- the first is robustness and next is real time implementation. The second contribution of this thesis is implementation of the proposed algorithm on BeagleBone Black and Rapsberry pi-2, which are low cost, low-power single-board computers. This provides a proof-of-concept of real time computation. Thus, the thesis improves the accuracy of the state of the art path detection and provides means of real time implementation on mobile platforms.
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    ItemOpen Access
    D-latch based low power memory design
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2015) Tripathi, Saurabh; Mishra, Biswajit
    Low power consumption is the main attraction of the digital circuit design in the Sub threshold region of operation. In this region of operation less energy is consumed for active operation and less leakage power is dissipated than higher voltage alternatives. As a trade-off circuits operate slowly because the supply voltage is less than the threshold voltage of the transistors. Sub-threshold operation is considered as an effective solution in designs where low power consumption is the prime concern and operating speed can be sacrificed. The sub-threshold systems need the same voltage level operated memory design. Also, the sub-threshold memory design must be robust in terms of SNM (signal to noise margin) as the operating supply voltage is few hundreds of millivolts depending on technology node. This demands the architecture that ensures the effective data read/write operation under all critical conditions. This research work mainly focuses on D-Latch based 128 Byte full custom memory array and memory controller design. Starting with different latch architectures’ minimum operating supply voltage comparison, the complete Byte addressable memory design flow including row/column decoder design, memory controller design has been discussed. The complete layout of the memory, performance results under an application and its different parameters have also been included in the report. All the design parameters and the simulation results are produced for 0.18μm process.
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    ItemOpen Access
    GPU-accelerated method of moments
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2015) Soni, Pushtivardhan; Zaveri, Mazad S.
    This work considers the use of commodity graphics processing units (GPUs) for accelerating run-time critical phase of method of moments (MoM) which is a widely used computational electromagnetic (CEM) technique for solving electromagnetic problems governed by an electric field integral equation (EFIE), and ideally suited for radiation and scattering problems. To this end, scattering analysis of metallic bodies with arbitrary shape using standard Rao-Wilton-Glisson (RWG) basis and weighting functions which is a good tradeoff between accuracy and complexity, is considered for the serial and parallel implementations. Among the phases of MoM—assembling impedance matrix and excitation vector, and solving matrix equation—impedance matrix assembly is the most compute intensive phase, and involves massive data-based parallelism; computation of each matrix element requires execution of a common program with unique data set. Therefore the impedance matrix assembly phase is subjected to the GPU acceleration using CUDA that supports single instruction, multiple data (SIMD) paradigm. The results computed shows a good agreement with the reference values computed with commercial software package such as FEKO. From the performance viewpoint, the GPU-based implementation shows a significant speedups over the CPU-only implementation. The linear growth of speedup with respect to number of CUDA threads used to compute matrix element conforms the scalability of the implementation, and indicates the feasibility of greater speedups for larger problems. The peak speedup for the impedance matrix assembly phase of MoM was measured to be about 30 that turn up about 4× faster execution when considering total MoM solution process for the problem and hardware considered. In addition, the comprehensive treatment of the scattering problem in functional analysis framework and the detailed implementation of MoM make this work useful for developing other accelerated implementations of other computational electromagnetic (CEM) methods (i.e., FDTD, FEM).