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Dev Growth Differ. 2013 May;55(4):523-49. doi: 10.1111/dgd.12054. Epub 2013 Apr 7.

Image processing and recognition for biological images.

Author information

1
Department of Advanced Information Technology, Kyushu University, 744 Motooka, Nishi, Fukuoka, 819-0395, Japan. uchida@ait.kyushu-u.ac.jp

Abstract

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target.

PMID:
23560739
PMCID:
PMC3746120
DOI:
10.1111/dgd.12054
[Indexed for MEDLINE]
Free PMC Article

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