Abstract
This paper is focused on a description of a new method of detecting continuities in a binary image. The detecting method is called “Binary Large Object” (BLOB). A new algorithm with other elementary parameters, as processing speed and memory capability, are described here. The developed BLOB method with described algorithms is implemented in MATLAB. The simulation of the algorithms is tested in different conditions, with the time dependences determination. The research results of the computing time or the BLOB memory demand during computation are presented as well. The developed BLOB method is usable as one of the elementary image processing methods of the field detection dependencies in the images, like pattern recognition or OCR algorithm.
Highlights
A new approach of an innovative method for continuity detection in the binary image will be presented in this paper
The advantages of the innovative Binary Large Object” (BLOB) method compared to the classical original method of the BLOB image processing methodology are described here by presented examples and the program algorithm steps with pixel figures
The time consuming BLOB method verification by different object area sizes is over 8 ms faster for the innovative BLOB method comparing to the classical BLOB method without a crucial dependency on different area sizes
Summary
A new approach of an innovative method for continuity detection in the binary image will be presented in this paper. The method is called “Binary Large Object” (BLOB). The developed innovative method is represented by developed algorithms for continuous area localization in the binary image. The results are compared with other methods for continuous area localization. This comparison is focused on processing the speed and Random Access Memory (RAM) memory usage in the process managing. Both compared algorithms are implemented in MATLAB. The discussion of the algorithms is performed on two test sets of binary images and pre-specified conditions
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