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SoC Design Of A Novel Cluster-Based Approach for Real-Time Lane Detection in Low Quality Images

Published: 05 September 2017 Publication History

Abstract

In this paper, we present a novel System on Chip design for real time lane detection approach on low-quality grayscale images. The proposed method leverages the sequential read out from image sensors to progressively build clusters. The decision to allocate pixels to existing lines (clusters) is made on the fly as pixels flow from the image sensor into the system. We propose a hardware/software partitioning that places low-level computational intensive parts in a pipelined chain in hardware. The pipeline first applies morphological operations on incoming images to enhance their quality. Later canny edge detection followed by Probabilistic Hough Transform is used for accurate line detection. The lines are then filtered and clustered before being fitted into road lanes using weighted least squares method. We prototype our design on a system on FPGA with a precision above 90% and demonstrate a speedup of 2.09x compared to a software only implementation on an embedded processor.

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Cited By

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  • (2019)Neuromorphic Image Sensor Design with Region-Aware Processing2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI.2019.00089(459-464)Online publication date: Jul-2019
  • (2018)Transparent Acceleration of Image Processing Kernels on FPGA-Attached Hybrid Memory Cube Computers2018 International Conference on Field-Programmable Technology (FPT)10.1109/FPT.2018.00069(342-345)Online publication date: Dec-2018
  • (2018)Design of a Reconfigurable 3D Pixel-Parallel Neuromorphic Architecture for Smart Image Sensor2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW.2018.00110(786-7868)Online publication date: Jun-2018

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  1. SoC Design Of A Novel Cluster-Based Approach for Real-Time Lane Detection in Low Quality Images

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    ICDSC 2017: Proceedings of the 11th International Conference on Distributed Smart Cameras
    September 2017
    221 pages
    ISBN:9781450354875
    DOI:10.1145/3131885
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 05 September 2017

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    Author Tags

    1. Edge Detection
    2. Probabilistic Hough Transform
    3. Region of Interest
    4. Segmentation

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    View all
    • (2019)Neuromorphic Image Sensor Design with Region-Aware Processing2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI.2019.00089(459-464)Online publication date: Jul-2019
    • (2018)Transparent Acceleration of Image Processing Kernels on FPGA-Attached Hybrid Memory Cube Computers2018 International Conference on Field-Programmable Technology (FPT)10.1109/FPT.2018.00069(342-345)Online publication date: Dec-2018
    • (2018)Design of a Reconfigurable 3D Pixel-Parallel Neuromorphic Architecture for Smart Image Sensor2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW.2018.00110(786-7868)Online publication date: Jun-2018

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