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Image processing and recognition for biological images

机译:生物图像的图像处理和识别

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摘要

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.
机译:本文回顾了图像处理和模式识别技术,这将有助于分析生物图像。尽管本文未提供其技术细节,但有可能掌握其主要任务以及处理这些任务的典型工具。图像处理是一个很大的研究领域,可以提高输入图像的可见性并从中获取一些有价值的信息。作为图像处理的主要任务,本文介绍了灰度转换,二值化,图像滤波,图像分割,视觉对象跟踪,光流和图像配准。图像模式识别是一种将输入图像分类为预定义类别之一的技术,并且具有很大的研究领域。本文概述了它的两个主要模块,即特征提取模块和分类模块。在整个论文中,将强调由于噪声,变形等原因,即使对于最先进的图像处理和模式识别技术,生物图像也是一个非常困难的目标。本文有望成为桥接生物学的一个教程指南。和图像处理研究人员的进一步合作,以解决这一难题。

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