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Proceedings Paper

Method for stitching microbial images using a neural network
Author(s): E. A. Semenishchev; V. V. Voronin; V. I. Marchuk; I. V. Tolstova
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Paper Abstract

Currently an analog microscope has a wide distribution in the following fields: medicine, animal husbandry, monitoring technological objects, oceanography, agriculture and others. Automatic method is preferred because it will greatly reduce the work involved. Stepper motors are used to move the microscope slide and allow to adjust the focus in semi-automatic or automatic mode view with transfer images of microbiological objects from the eyepiece of the microscope to the computer screen. Scene analysis allows to locate regions with pronounced abnormalities for focusing specialist attention. This paper considers the method for stitching microbial images, obtained of semi-automatic microscope. The method allows to keep the boundaries of objects located in the area of capturing optical systems. Objects searching are based on the analysis of the data located in the area of the camera view. We propose to use a neural network for the boundaries searching. The stitching image boundary is held of the analysis borders of the objects. To auto focus, we use the criterion of the minimum thickness of the line boundaries of object. Analysis produced the object located in the focal axis of the camera. We use method of recovery of objects borders and projective transform for the boundary of objects which are based on shifted relative to the focal axis. Several examples considered in this paper show the effectiveness of the proposed approach on several test images.

Paper Details

Date Published: 23 May 2017
PDF: 7 pages
Proc. SPIE 10221, Mobile Multimedia/Image Processing, Security, and Applications 2017, 102210O (23 May 2017); doi: 10.1117/12.2262498
Show Author Affiliations
E. A. Semenishchev, Don State Technical Univ. (Russian Federation)
V. V. Voronin, Don State Technical Univ. (Russian Federation)
V. I. Marchuk, Don State Technical Univ. (Russian Federation)
I. V. Tolstova, Don State Technical Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10221:
Mobile Multimedia/Image Processing, Security, and Applications 2017
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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