Abstract
The storage requirements for component labeling and fea ture extraction operations are unknown a priori. Whenever large images are processed, many labels, and thus a large amount of storage, may be required, making hardware implementation difficult. The proposed labeling procedure eliminates memory overflow by enabling the reuse of memory locations in which features of nonactive labels had been stored. The storage requirement for the worst case conditions is analyzed and is shown to be realizable. The basic procedure can be implemented in two modes, an interrupted mode or a parallel mode. A hardware design is presented.
| Original language | English |
|---|---|
| Pages (from-to) | 116-121 |
| Number of pages | 6 |
| Journal | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Volume | PAMI-7 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 1985 |
| Externally published | Yes |
Keywords
- Component labeling
- feature extraction
- image processing
- visual inspection
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics
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