Efficient scan mask techniques for connected components labeling algorithm
<p>Abstract</p> <p>Block-based connected components labeling is by far the fastest algorithm to label the connected components in 2D binary images, especially when the image size is quite large. This algorithm produces a decision tree that contains 211 leaf nodes with 14 levels for...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2011-01-01
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| Series: | EURASIP Journal on Image and Video Processing |
| Subjects: | |
| Online Access: | http://jivp.eurasipjournals.com/content/2011/1/14 |
| _version_ | 1811315056428711936 |
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| author | Sutheebanjard Phaisarn Premchaiswadi Wichian |
| author_facet | Sutheebanjard Phaisarn Premchaiswadi Wichian |
| author_sort | Sutheebanjard Phaisarn |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Block-based connected components labeling is by far the fastest algorithm to label the connected components in 2D binary images, especially when the image size is quite large. This algorithm produces a decision tree that contains 211 leaf nodes with 14 levels for the depth of a tree and an average depth of 1.5923. This article attempts to provide a faster method for connected components labeling. We propose two new scan masks for connected components labeling, namely, the pixel-based scan mask and the block-based scan mask. In the final stage, the block-based scan mask is transformed to a near-optimal decision tree. We conducted comparative experiments using different sources of images for examining the performance of the proposed method against the existing methods. We also performed an average tree depth analysis and tree balance analysis to consolidate the performance improvement over the existing methods. Most significantly, the proposed method produces a decision tree containing 86 leaf nodes with 12 levels for the depth of a tree and an average depth of 1.4593, resulting in faster execution time, especially when the foreground density is equal to or greater than the background density of the images.</p> |
| first_indexed | 2024-04-13T11:23:27Z |
| format | Article |
| id | doaj.art-a6b34349cd664321afc1bc4963dadf1c |
| institution | Directory Open Access Journal |
| issn | 1687-5176 1687-5281 |
| language | English |
| last_indexed | 2024-04-13T11:23:27Z |
| publishDate | 2011-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-a6b34349cd664321afc1bc4963dadf1c2022-12-22T02:48:46ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-51761687-52812011-01-012011114Efficient scan mask techniques for connected components labeling algorithmSutheebanjard PhaisarnPremchaiswadi Wichian<p>Abstract</p> <p>Block-based connected components labeling is by far the fastest algorithm to label the connected components in 2D binary images, especially when the image size is quite large. This algorithm produces a decision tree that contains 211 leaf nodes with 14 levels for the depth of a tree and an average depth of 1.5923. This article attempts to provide a faster method for connected components labeling. We propose two new scan masks for connected components labeling, namely, the pixel-based scan mask and the block-based scan mask. In the final stage, the block-based scan mask is transformed to a near-optimal decision tree. We conducted comparative experiments using different sources of images for examining the performance of the proposed method against the existing methods. We also performed an average tree depth analysis and tree balance analysis to consolidate the performance improvement over the existing methods. Most significantly, the proposed method produces a decision tree containing 86 leaf nodes with 12 levels for the depth of a tree and an average depth of 1.4593, resulting in faster execution time, especially when the foreground density is equal to or greater than the background density of the images.</p>http://jivp.eurasipjournals.com/content/2011/1/14connected componentsimage processinglabeling algorithmlinear time algorithmpattern recognition. |
| spellingShingle | Sutheebanjard Phaisarn Premchaiswadi Wichian Efficient scan mask techniques for connected components labeling algorithm EURASIP Journal on Image and Video Processing connected components image processing labeling algorithm linear time algorithm pattern recognition. |
| title | Efficient scan mask techniques for connected components labeling algorithm |
| title_full | Efficient scan mask techniques for connected components labeling algorithm |
| title_fullStr | Efficient scan mask techniques for connected components labeling algorithm |
| title_full_unstemmed | Efficient scan mask techniques for connected components labeling algorithm |
| title_short | Efficient scan mask techniques for connected components labeling algorithm |
| title_sort | efficient scan mask techniques for connected components labeling algorithm |
| topic | connected components image processing labeling algorithm linear time algorithm pattern recognition. |
| url | http://jivp.eurasipjournals.com/content/2011/1/14 |
| work_keys_str_mv | AT sutheebanjardphaisarn efficientscanmasktechniquesforconnectedcomponentslabelingalgorithm AT premchaiswadiwichian efficientscanmasktechniquesforconnectedcomponentslabelingalgorithm |