Extraction of Homogeneous Fine-Grained Texture Segments in Visual Images

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00478807" target="_blank" >RIV/67985807:_____/17:00478807 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.14311/NNW.2017.27.024" target="_blank" >http://dx.doi.org/10.14311/NNW.2017.27.024</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2017.27.024" target="_blank" >10.14311/NNW.2017.27.024</a>

Result language
angličtina
Original language name
Extraction of Homogeneous Fine-Grained Texture Segments in Visual Images
Original language description
A new heuristic algorithm is proposed for extraction of all homogeneous fine-grained texture segments present in any visual image. The segments extracted by this algorithm should comply with human understanding of homogeneous fine-grained areas. The algorithm sequentially extracts segments from more homogeneous to less homogeneous ones. The algorithm belongs to a region growing approach. So, for each segment, an initial seed point of this segment is found. Then, from this initial pixel, the segment begins to expand occupying its adjacent neighborhoods. This procedure of expansion of the segment continues till the segment reaches its borders. The algorithm examines neighboring pixels using texture features extracted in the image by means of a set of texture windows. The segmentation process terminates when the image contains no more sizable homogeneous segments. The segmentation procedure is fully unsupervised, i.e., it does not use a priori knowledge on either the type of textures or the number of texture segments in the image. Using black and white natural scenes, a series of experiments demonstrates efficiency of the algorithm in extraction of homogeneous fine-grained texture segments and the segmentation looks reasonable ”from a human point of view”.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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