Robust Focusing using Orientation Code Matching

Yuan Li, Isao Ohmura, Hidenori Takauji, Shun'ichi Kaneko, Takayuki Tanaka


This paper proposes a novel scheme for image focusing by introducing a new focus measure based on self-matching methods. A unique pencil-shaped profile is identified by comparing the similarity between all patterns extracted around the same position in each scene. Based on this profile, a new criterion function called Complementary Pencil Volume (hereafter CPV) is defined to evaluate focused or defocused scenes based on similarity rate of self-matching, which visually represents the volume of a pencil-shaped profile. Among matching methods, Orientation Code Matching (hereafter OCM) is recommended due to its invariance with regards to illumination and contrasts. Several experiments using a telecentric lens are implemented to demonstrate the efficiency of proposed measures. Outstandingly, comparing Orientation Code Matching-based (hereafter OCM-based) focus measure with conventional focus measures shows that OCM-based focus measure is robust against changes of illuminations and contrast. Using this method, depth is measured by comparing the focused and defocused region in the scenes both under high and low illumination conditions.


OCM; CPV; Local-based search algorithm; III conditioning; Pan-focused Image; Depth measurement; Robustness; Focusing

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