Determination of volume characteristics of cells from dynamical microscopic image

The algorithm for the determination of 3D-characteristics of a dynamic biological object based on the recovery of a stereo pair was proposed. Images for stereo pair construction were obtained via a single camera before and after the displacement of the object. The algorithm is based on the example of living one-celled organisms

Reliance on High Technologies

The Department of Physics, Mathematics and Informatics of the National Academy of Sciences of Belarus coordinates fundamental and applied work on priority scientific directions with account of the world science trends, available potential and the country's economy demands. The Department includes 3 state research institution

Reliance on High Technologies

The Department of Physics, Mathematics and Informatics of the National Academy of Sciences of Belarus coordinates fundamental and applied work on priority scientific directions with account of the world science trends, available potential and the country's economy demands. The Department includes 3 state research institution

Image Enhancement by Fast Distance Transform

A new and fast non-Euclidean distance transform is presented which belongs to a class of raster scanning methods. The proposed algorithm is about 30% faster than other similar techniques and shows good results when applying to solve an image enhancement tas

Interpreting images of line drawings: a tutorial presented at the 16th International conference on pattern recognition (ICPR), Quebec city, Canada, 11th August 2002

While development continues, multimedia tools for planning and recording the results of work on complex engineering products and projects are now widely available. These tools can significantly improve communication within project teams but suffer from an input bottleneck: most of the necessary 3D and other product/design information is readily available, but is typically in the form of paper documents, particularly drawings. Manual input of drawings into CAD, GIS and other systems is a possibility, albeit a slow and expensive one. This tutorial will focus on techniques for the interpretation of images of line drawings. It will cover the low level processes involved in and issues to be addressed during the segmentation and geometric description of line drawing images, consider the extraction of intermediate level entities (e.g. text, dimensions, crosshatched areas and physical outlines) and present and discuss current techniques for ground-truthing and performance evaluation. Prof. Sergey Ablameyko is Head of the Image Processing and Recognition Laboratory and Deputy Director of the Institute of Engineering Cybernetics of the National Academy of Sciences of Belarus. Dr. Tony Pridmore is Senior Lecturer in Computer Science, School of Computer Science and IT, University of Nottingham, UK, where he is a senior member of the Image Processing and Interpretation Research Group. Prof. Ablameyko and Dr. Pridmore have a combined 20 years experience of line drawing image interpretation. They have published some 100 papers in the area (independently and together) and several books, most notably S. Ablameyko & T.P. Pridmore, "Machine Interpretation of Line Drawing Images" (Springer-Verlag, 2000)

Person re-identification accuracy improvement by training a CNN with the new large joint dataset and re-rank

The paper is aimed to improve person re-identification accuracy in distributed video surveillance systems based on constructing a large joint image dataset of people for training convolutional neural networks (CNN). For this aim, an analysis of existing datasets is provided. Then, a new large joint dataset for person re-identification task is constructed that includes the existing public datasets CUHK02, CUHK03, Market, Duke, MSMT17 and PolReID. Testing for re-identification is performed for such frequently cited CNNs as ResNet-50, DenseNet121 and PCB. Re-identification accuracy is evaluated by using the main metrics Rank, mAP and mINP. The use of the new large joint dataset makes it possible to improve Rank1 mAP, mINP on all test sets. Re-ranking is used to further increase the re-identification accuracy. Presented results confirm the effectiveness of the proposed approach

Detection patterns of living cells from its aggregation on the digital image

One of the important problem of modern direction of cytological image analysis is cells segmentation. There are many algorithms in this field. But image properties and methods of cell investigation are changing every day. Today most perspective direction of cytological image analysis is lifing cells investigation. Such images lead to many troubles for cells analysis. In this paper we are proposed solution of one such problems: pattern extraction of cells from its aggregation

From computer vision to document recognition or using labeling technique for map interpretation

This paper considers an application of computer vision notions for document recognition problem. The well developed in computer vision labeling technique is applied for interpretation of black-and-white layers of geographical maps. The knowledge base and main relations between cartographical objects and segments are extracted and described. Map-drawing interpretation process by using labeling technique is proposed. The suggested approach allows to increase a level of automatic object recognitio