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Algorithms for computing distances to object pixels on binary images

N.L. Kazanskiy, V.V. Myasnikov, R.V. Khmelev

Image Processing Systems Institute of RAS

 PDF, 294 kB

Pages: 134-139.

Full text of article: Russian language.

Abstract:
One of the most important tasks in image processing is the task of performing the measurements on the image [1], in particular, measuring the distances between the image points. Let us assume that there is a binary picture, in this picture the values “0” will be referred to as the background, and the values “1” will be referred to as the object. For each point of the background, it is required to find the distance (in pixels) to the nearest point of the object (we will call it the snap distance), and this shall be done in a minimum number of operations. This problem arises, for example, when an object is compared with the standard in terms of deviation of the contours [2]. This article describes two algorithms for solving this problem.

Citation:
Kazanskiy NL, Myasnikov VV, Khmelev RV. Algorithms for computing distances to object pixels on binary images. Computer Optics 2000; 20: 134 - 139.

References:

  1. Soifer VA. Problems of digital image processing and computer optics. Transcripts of the academic report made at the meeting of the RAS Presidium on October 19, 1999. Computer Optics 1999; 19: 6-20.
  2. Kazanskiy NL, Khmelev RV. Comparison of an object and a sample for the deviation of the contours // Computer Optics 2000; 20: 134-139.

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