Automated Classification of Bitmap Images using Decision Trees
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| Natura: | Artículo científico |
| Lingua: | en |
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Instituto Politécnico Nacional
2011
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| _version_ | 1876437558743793664 |
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| author | Pavel Surynek |
| author_facet | Pavel Surynek |
| contents | Automated Classification of Bitmap Images using Decision Trees Pavel Surynek Ivana Lukšová Computación learning learning decision trees decision trees Image classification The paper addresses the design of a method forautomated classification of bitmap images into classes describedby the user in natural language. Examples of such naturallydefined classes are images depicting buildings, landscape, artisticimages, etc. The proposed classification method is based on theextraction of suitable attributes from a bitmap image such ascontrast, histogram, the occurrence of straight lines, etc.Extracted attributes are subsequently processed by a decisiontree which has been trained in advance. A performedexperimental evaluation with 5 classification classes showed thatthe proposed method has the accuracy of 75%-85%. The designof the method is general enough to allow the extension of the setof classification classes as well as the number of extractedattributes to increase the accuracy of classification. 2011 artículo científico 1870-9044 https://www.redalyc.org/articulo.oa?id=402640458002 en http://www.redalyc.org/revista.oa?id=4026 Polibits application/pdf Instituto Politécnico Nacional Polibits (México) Vol.44 |
| format | Artículo científico |
| id | redalyc_402640458002 |
| institution | Redalyc |
| language | en |
| publishDate | 2011 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Automated Classification of Bitmap Images using Decision Trees Pavel Surynek Computación learning learning decision trees decision trees Image classification Automated Classification of Bitmap Images using Decision Trees Pavel Surynek Ivana Lukšová Computación learning learning decision trees decision trees Image classification The paper addresses the design of a method forautomated classification of bitmap images into classes describedby the user in natural language. Examples of such naturallydefined classes are images depicting buildings, landscape, artisticimages, etc. The proposed classification method is based on theextraction of suitable attributes from a bitmap image such ascontrast, histogram, the occurrence of straight lines, etc.Extracted attributes are subsequently processed by a decisiontree which has been trained in advance. A performedexperimental evaluation with 5 classification classes showed thatthe proposed method has the accuracy of 75%-85%. The designof the method is general enough to allow the extension of the setof classification classes as well as the number of extractedattributes to increase the accuracy of classification. 2011 artículo científico 1870-9044 https://www.redalyc.org/articulo.oa?id=402640458002 en http://www.redalyc.org/revista.oa?id=4026 Polibits application/pdf Instituto Politécnico Nacional Polibits (México) Vol.44 |
| title | Automated Classification of Bitmap Images using Decision Trees |
| topic | Computación learning learning decision trees decision trees Image classification |
| url | https://www.redalyc.org/articulo.oa?id=402640458002 |