Title :
Efficient inscribing of noisy rectangular objects in scanned images
Author_Institution :
Microsoft Res., Redmond, WA, USA
Abstract :
Objects identification in images is generally hard unless the objects are simple geometric shapes such as circles, rectangles, have very particular properties. Even simple geometric shapes can be hard to identify if they deviate even a little from the ideal. We examine the question of identifying and segmenting noisy rectangles, where edges may be ragged, corners may be missing and so on. We test the robustness of our scheme on receipts and small documents obtained from real scans.
Keywords :
edge detection; feature extraction; image scanners; image segmentation; object detection; geometric shape; image representation; noisy rectangle segmentation; objects identification; ragged edge; real scan; scanned image; Image segmentation; Large Hadron Collider; Least squares approximation; Noise shaping; Object segmentation; Pixel; Programmable control; Robustness; Shape; Testing;
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
Print_ISBN :
0-7803-8554-3
DOI :
10.1109/ICIP.2004.1421584