This paper proposes a novel focus measure based on self-matching methods. A unique pencil-shaped profile is identified by comparing the similarity between patterns extracted around their neighborhood in each scene. Based on this, a new criterion function, CPV, is defined to evaluate focused or defocused scenes. OCM is recommended due to its invariance with regards to contrasts. Experiments using a telecentric lens are implemented to demonstrate the efficiency of proposed measure. Comparing OCM-based focus measure with conventional focus measures shows that OCM-based CPV is robust against illuminations. Using this method, pan-focused images are composed and depth information is represented.
This paper has proposed a novel and robust scheme of image focusing by introducing a new measure of focusing based on Orientation Code Matching.(hereinafter,OCM) A unique pencil-shape profile has been found through comparing the similarity between any patterns extracted at the same position within their own scenes. Based on this profile, a new evaluation function, named Complemental Pencil Volume, (hereinafter, CPV), is defined and calculated to represent local sharpness of images, either in or out of focus. Then through a designed local-scope searching algorithm, the maximum of CPV, which corresponds to the just focused image, is searching in this schema. The proposed method of focusing can be applied to cases of ill-condition with low contrast observations. Experiment results show that the OCM-based focusing is very robust to change of brightness and even more irregularities in the real imaging system, like dark condition and so on.
This paper has mainly discussed about two problems, object focusing and depth measurement. First, we propose a novel and robust scheme of image focusing by introducing a new measure of focusing based on Orientation code matching. A new evaluation function, named Complemental pencil volume, CPV, is defined and calculated to represent local sharpness of images, either in or out of focus, by comparing the similarity between any patterns extracted at the same position within their own scenes. An identified and unique maximum or peek, which of ill-condition scenes with low contrast observations. Experiments show that the OCM-based focusing is very robust to change in brightness, and to even more irregularities in the real imaging system, like dark condition. Second, based on this robust focusing technique, we applied it to an image sequence of an object surface to measure the depth of profile. A simple plane object surface has been implemented to demonstrate the basic approach. The results showed the successful and precision depth measurement of this object.
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