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Sergey A. Turko; Ilia V. Safonov (2016)
Publisher: Общество с ограниченной ответственностью «Корпорация Интел Групп»
Journal: Системы управления, связи и безопасности
Languages: Russian
Types: Article
Subjects:

Classified by OpenAIRE into

ACM Ref: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Some visual tracking tasks are unable to operate stable for video with blurred frames because feature points detection is degraded on blur images. In the paper we concentrate on blurriness due to refocusing of camera optical system of mobile devices. Our aim is evaluation of influence of blur and sharpening on Harris corner and FAST keypoints detectors. We propose a quality criterion in order to be able to make numerical assessment of the influence. For enhancement of blurred frames we investigate two sharpening filters: local tone mapping decreases of edge transition slope length, unsharp mask via bilateral filter increases local contrast along edges. On data from KITTI Vision Benchmark Suite as well as video captured by smartphone we demonstrate that sharpening improves feature points detection for both Harris corner and FAST methods. A positive impact for FAST is significant, it may improve robustness of various computer vision systems.
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