DeVille Julian S, Kihara Daisuke, Sit Atilla
1Department of Mathematics and Statistics, Eastern Kentucky University, 521 Lancaster Ave., Richmond, 40475 KY USA.
2Department of Biology Sciences, Purdue University, 249 S Martin Jischke Dr, West Lafayette, 47907 IN USA.
Source Code Biol Med. 2020 Feb 10;15:1. doi: 10.1186/s13029-020-0077-1. eCollection 2020.
Direct comparison of 2D images is computationally inefficient due to the need for translation, rotation, and scaling of the images to evaluate their similarity. In many biological applications, such as digital pathology and cryo-EM, often identifying specific local regions of images is of particular interest. Therefore, finding invariant descriptors that can efficiently retrieve local image patches or subimages becomes necessary.
We present a software package called Two-Dimensional Krawtchouk Descriptors that allows to perform local subimage search in 2D images. The new toolkit uses only a small number of invariant descriptors per image for efficient local image retrieval. This enables querying an image and comparing similar patterns locally across a potentially large database. We show that these descriptors appear to be useful for searching local patterns or small particles in images and demonstrate some test cases that can be helpful for both assembly software developers and their users.
Local image comparison and subimage search can prove cumbersome in both computational complexity and runtime, due to factors such as the rotation, scaling, and translation of the object in question. By using the 2DKD toolkit, relatively few descriptors are developed to describe a given image, and this can be achieved with minimal memory usage.
由于需要对图像进行平移、旋转和缩放以评估其相似度，二维图像的直接比较在计算上效率低下。在许多生物学应用中，如数字病理学和冷冻电镜，通常识别图像的特定局部区域特别重要。因此，找到能够有效检索局部图像块或子图像的不变描述符变得很有必要。
我们提出了一个名为二维克拉夫楚克描述符的软件包，它允许在二维图像中进行局部子图像搜索。这个新工具包在每个图像上仅使用少量不变描述符来进行高效的局部图像检索。这使得能够查询一幅图像并在潜在的大型数据库中局部比较相似模式。我们表明，这些描述符似乎对于在图像中搜索局部模式或小颗粒很有用，并展示了一些对组装软件开发人员及其用户都有帮助的测试用例。
由于诸如相关对象的旋转、缩放和平移等因素，局部图像比较和子图像搜索在计算复杂度和运行时可能都很麻烦。通过使用2DKD工具包，只需开发相对较少的描述符来描述给定图像，并且这可以在最小内存使用的情况下实现。
