Sergey Ablameyko

Morphological segmentation of histology cell images

Two algorithms for segmentation of cell images are proposed. They have a unique part that contains computation of morphological gradient to extract object borders and thinning the obtained borders to get a line of one-pixel thickness. For this task, we propose the fast gray-scale thinning algorithm that is based on the idea of the analysis of binary image layers. Then, the obtained one-pixel lines are used to extract cells and compute their characteristics. The algorithms based on morphological and split/merge segmentation are developed and used for this task.

Straight-line-based primitive extraction in grey-scale object recognition

A method for extraction of straight-line-based primitives is proposed. It is based on a bottom-up approach that extracts linear primitives first, then line segments, that are grouped in straight lines. Based on the extracted lines, quadrangles are detected and further approximated by rectangles. The extracted primitives are used in object recognition. The proposed approach provides a good relation between the complexity of extracted primitives and the complexity of algorithm itself, that allows it to be used in industrial applications.

Medical image registration based on SURF detector

A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision.

Vectorization and Representation of Large-Size 2-D Line-Drawing Images

Abstract This paper proposes an approach to the vectorization and representation of large-size document images. The approach is based on a modified run-length image representation and line-by-line processing scheme with a limited amount of image line stored in memory. Within this approach fast one-pass algorithms for thinning and transformation of a large-size thinned image in vector form are suggested. A hierarchical data structure for the representation of these images in vector form, which stores in compact form all the needed information about connected components, segments, and feature points, is suggested. The process steps for obtaining this data structure are described. The defects which can exist in the vector representation are extracted and an algorithm for their reduction is given. Experimental results are also shown.

Fast Line and Rectangle Detection by Clustering and Grouping

Fast algorithms to detect lines and rectangles in grey-scale images are proposed. At first, a contour image is obtained by the modified edge detection scheme. The linear primitives are extracted in the contour image and joined into line segments by cluster analysis method. The line merging algorithm is developed to get straight lines from segments. Algorithm to detect rectangles from the extracted straight lines is suggested. The developed algorithms are fast and permit to get the qualitative result.

RECOGNITION OF ENGINEERING DRAWING ENTITIES: REVIEW OF APPROACHES

Recognition of engineering drawing entities is one of the most difficult stages in engineering drawing interpretation and many attempts to recognize various types of ED entities have been made. In this paper, we review algorithms for the recognition of ED entities, especially dimensions and crosshatching areas. For the recognition of dimensions, we analyze how dimension texts can be separated from graphics and how arrowheads of dimension lines are recognized. We also analyze the recent systems of ED interpretation. Finally, future tasks are discussed.

Gray-scale thinning by using a pseudo-distance map

In this paper, the algorithm for thinning of grey-scale images is proposed that is based on a pseudo-distance map (PDM). The PDM is a simplified distance map of gray-scale image and uses only that features of image and objects that are necessary to build a skeleton. The algorithm works fast for large gray-scale images and allows constructing a high quality skeleton

From cell image segmentation to differential diagnosis of thyroid cancer

An approach for cytologic diagnosis of thyroid cancer with the help of automatic morphometry is proposed. This approach is based on a developed computer analyser of images that is aimed at: automated processing and binarization of colour images; automatic raster-to-vector transformation and formation of biological objects; morphometric assessment of biological objects by quantitative parameters characterizing the changes of cell nuclei; building of an expert system to aid the diagnosis of thyroid cancer.

Algorithms for recognition of the main engineering drawing entities

The paper introduces the main principles of automatic interpretation of engineering drawing images. The technology of ED interpretation is proposed based on the introduced principles. The algorithms for automatic recognition of the main ED entities: line types, circular arcs, blocks, crosshatched areas and dimensions are proposed. They have been verified experimentally in the whole ED interpretation technology and show good results.

Computer-aided cartographical system for map digitizing

The authors present a PC-based cartographical system to digitize maps. A memory restriction made us develop special technologies and techniques to digitize large-sized map-drawings. The combination of manual digitizing and labeling with automatic vectorization and recognition, and interactive editing allowed us to get satisfactory time characteristics for digitizing complex maps. To process automatically scanned maps in a restrictive computer memory, an effective pipeline oriented scheme and new techniques have been developed. A new process called object labeling has been introduced to speed up the interpretation process. An output database structure has been suggested to store all needed information about the map.<<ETX>>