Abstract
In the camera manufacturing, there exist dusts, fingerprints, and water spots on the image sensor and lens. Hence, the resultant effects of darker region is called blemish, which causes a significant reduction in camera quality. The shapes of blemishes are diverse and irregular. Traditional method detects blemishes using image median filtering in a single direction which leads to false alarm and mis-detection for images with high level of noises. Thus, we present a novel filtering method for blemish detection, which utilizes four directional filters in the 0, 45, 90, 135 degrees directions. Compared to the conventional single direction filter, the multidirectional filters take into account more spatial information to more accurately detect blemishes for both weak and strong blemishes. Moreover, the proposed method uses a new adaptive threshold to better accommodate different image noise levels automatically. Experimental results on two batches of production samples (600 images) show the effectiveness of the proposed method over the conventional method.
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Acknowledgments
This work was supported in part by the Shenzhen Emerging Industries of the Strategic Basic Research Project (No. JCYJ20160226191842793), and the National Natural Science Foundation of China (No. 61602312, 61602314, 61620106008).
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Wang, K., Hung, KW., Jiang, J. (2017). A Novel Blemish Detection Algorithm for Camera Quality Testing. In: Li, G., Ge, Y., Zhang, Z., Jin, Z., Blumenstein, M. (eds) Knowledge Science, Engineering and Management. KSEM 2017. Lecture Notes in Computer Science(), vol 10412. Springer, Cham. https://doi.org/10.1007/978-3-319-63558-3_19
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DOI: https://doi.org/10.1007/978-3-319-63558-3_19
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