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<creators>
<creator>
<creatorName>Teodorescu, H.L.</creatorName>
<affiliation>Universitatea Tehnica „Gheorghe Asachi“, Iaşi, România</affiliation>
</creator>
<creator>
<creatorName>Rusu, M.</creatorName>
<affiliation>Universitatea Tehnică a Moldovei, Moldova, Republica</affiliation>
</creator>
</creators>
<titles>
<title xml:lang='en'>Image segmentation based on G-UN-MMS and heuristics. theoretical background and results</title>
</titles>
<publisher>Instrumentul Bibliometric National</publisher>
<publicationYear>2013</publicationYear>
<relatedIdentifier relatedIdentifierType='ISSN' relationType='IsPartOf'>1454-9069</relatedIdentifier>
<subjects>
<subject>algorithm</subject>
<subject>Gauss mixed model</subject>
<subject>Heuristic rules</subject>
<subject>Histogram</subject>
<subject>image segmentation</subject>
<subject>statistical model</subject>
<subject>Uniform noise mixed model</subject>
</subjects>
<dates>
<date dateType='Issued'>2013-01-01</date>
</dates>
<resourceType resourceTypeGeneral='Text'>Journal article</resourceType>
<descriptions>
<description xml:lang='en' descriptionType='Abstract'><p>We present the concept of image segmentation based on Gauss - Uniform Noise Mixed Models (GUN-MM) that we also introduce in this paper, the theoretical foundation of the segmentation method based on this model, results of the method on several classes of pictures, and a comparison with other methods. The proposed implementation of the G-UN-MM method has a simple and sound theoretical foundation and is not computationally demanding. It produces in many cases better segmentation results than other methods that are more computationally intensive.</p></description>
</descriptions>
<formats>
<format>application/pdf</format>
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