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| Detekcija rubova po Cannyju× | Izjednačavanje histograma× | |
|---|---|---|
| Područje | Računalni vid | Računalni vid |
| Obitelj | Machine learning | Machine learning |
| Godina nastanka≠ | 1986 | 1970s |
| Tvorac≠ | John Canny | Signal processing community |
| Vrsta≠ | Image gradient analysis | Contrast enhancement and preprocessing |
| Temeljni izvor≠ | Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), 679–698. DOI ↗ | Gonzalez, R. C., & Woods, R. E. (1992). Digital Image Processing. Addison-Wesley, 2nd edition, Chapter 3. link ↗ |
| Drugi nazivi | Canny operator, Canny edge detector | Histogram stretching, Contrast enhancement |
| Srodne | 5 | 5 |
| Sažetak≠ | The Canny edge detector, introduced by John Canny in 1986, is a multi-stage algorithm for identifying edges in digital images where significant intensity changes occur. Canny's method is optimal for step edges in additive Gaussian noise and remains the gold standard for edge detection in computer vision due to its mathematical elegance and practical effectiveness. | Histogram equalization is an image preprocessing technique that redistributes pixel intensities to improve contrast and visibility of details. By spreading the histogram of pixel values evenly across the available range, histogram equalization enhances images with poor contrast, making features more visually distinct and easier to process algorithmically. |
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