Title page for etd-0728117-232935


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URN etd-0728117-232935
Author Chih-hsuan Chang
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2016
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Hardware Design of Stereo Matching Based on Guided Image Filtering
Date of Defense 2017-07-28
Page Count 76
Keyword
  • stereo vision
  • stereo matching
  • depth information
  • mean filtering
  • guided image filtering
  • Abstract Stereo vision has many applications, including 3D movies and the recent advanced driver assisted systems (ADAS). In stereo vision, stereo matching of generating depth information is the most critical technique. In general, there are two categories of stereo matching methods: global and local. Local stereo matching methods are fast due to less computation while global methods can generate more accurate depth information at the cost of more computation complexity. This thesis uses local stereo matching methods with mean filtering and guided image filtering to improve the quality of depth information. A generic local stereo matching method can be divided into four stages: matching cost computation, cost aggregation, disparity selection, and disparity refinement. Guided image filtering can be applied to cost aggregation or disparity refinement. This thesis will study the impacts of using guided image filtering in different stereo matching stages. In hardware implementation for involved mean filtering, instead of the conventional integral image method, we use the moving-sum method with different data reading schemes of with line-based or stripe-based and compare the hardware resource requirement of internal memory buffers
    Advisory Committee
  • Pei-Yin Chen - chair
  • Kun-Chih Chen - co-chair
  • Ming-Chih Chen - co-chair
  • Shen-Fu Hsiao - advisor
  • Files
  • etd-0728117-232935.pdf
  • Indicate in-campus at 2 year and off-campus access at 5 year.
    Date of Submission 2017-08-28

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