Ranging Method of Binocular Stereo Vision Based on Random Ferns and NCC Template Matching

Ma, Weiping; Li, Wenxin; Cao, Peng-Xia

doi:10.1088/1755-1315/252/2/022149

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Methods Introduction 21 Fast Algorithm Principles1

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2024

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“…The fundamental concept of this algorithm revolves around comparing the grayscale values of a pixel with its surrounding neighboring pixels to determine whether it qualifies as a key point. Here's how FAST feature point detection operates [7][8] : Select a pixel point, denoted as P, within the image and record its grayscale value as Ip. Subsequently, set a predefined threshold value, denoted as t.…”

Section: Methods Introduction 21 Fast Algorithm Principlesmentioning

confidence: 99%

Geometric shape recognition based on FAST feature points and Hough transform

Kang,

Lu,

Zhang

et al. 2024

Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023)

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With the rapid development of computer vision and image processing, geometric shape recognition has become a highly regarded research area. This study aims to explore a method that combines the FAST feature point recognition algorithm with the Hough transform for fast and accurate recognition of geometric shapes in images, including lines, circles, and rectangles. The FAST feature point recognition algorithm is known for its speed and robustness in effectively detecting key points in images, while the Hough transform allows mapping these key points into parameter space, enabling us to detect and recognize specific geometric shapes. This research focuses on explaining the principles of the method, presenting experimental results, performance evaluations, and discussing future research directions.

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Section: Methods Introduction 21 Fast Algorithm Principlesmentioning

confidence: 99%