Abstract
With the development of automatic management for industrial manufactory, the applications involving computer-vision and pattern recognition are widely used. The advantages of these modern methods using database to store a large sequence of images for helping management have been widely recognized. However, the storage of massive images into a database may demand a large memory space and cause a slow access speed. To increase the utilization rate of storage space and improve the performance of the database, this paper proposes an image compression scheme which is learnt from video compression to remove temporal and spatial redundancy in the image sequence. The proposed scheme not only alleviates the above issues associated with image storage but also keeps the basic database operations valid to image access, such as, insert, delete and update. At the end of this paper, we use the result to solve the optimizing storage problem successfully for a packaging machine which is computer-vision based quality monitoring.
Supported by Major State Basic Research Development Program: 91120308.
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Ma, Z., Wang, X., Jiang, P., Jin, J., Guo, S. (2013). Sequential Record Based Compression for Massive Image Storage in Database. In: Gao, Y., et al. Web-Age Information Management. WAIM 2013. Lecture Notes in Computer Science, vol 7901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39527-7_12
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DOI: https://doi.org/10.1007/978-3-642-39527-7_12
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