In more elaborate cases, 3D volumetric images and 4D volumetric videos are provided. Imaging results are provided as still-images or videos. 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.ĭevelopment of imaging techniques, especially, microscopic imaging techniques, has made it possible to visualize various biological phenomena for biologists. 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 overviews its two main modules, that is, feature extraction module and classification module. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. 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 processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. 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. This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages.
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