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URN	etd-0728117-232935
Author	Chih-hsuan Chang
Author's Email Address	No Public.
Statistics	This thesis had been viewed 5342 times. Download 0 times.
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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