Access the full text.
Sign up today, get DeepDyve free for 14 days.
CH Chou, SY Chu, F Chang (2007)
Estimation of skew angles for scanned documents based on piecewise covering by parallelogramsPattern Recogn, 40
GS Lin, MK Chang, ST Chiu (2009)
A feature-based scheme for detecting and classifying video-shot transitions based on spatio-temporal analysis and fuzzy classificationInt J Pattern Recognit Artif Intell, 23
GS Lin, SK Chai, WC Yeh, YC Lin (2014)
Suspicious region detection and identification based on intra−/inter-frame analyses and fuzzy classifier for breast magnetic resonance imagingInt J Pattern Recognit Artif Intell, 28
Q Zhou, L Ma, M Celenk, D Chelberg (2005)
Content-based image retrieval based on ROI detection and relevance feedbackMultimedia Tools and Applications, 27
A Alaei, P Nagabhushan, U Pal, F Kimura (2016)
An efficient skew estimation technique for scanned documents: an application of piece-wise painting algorithmJ Pattern Recognit Res, 11
GS Lin, MK Chang, YL Chen (2011)
A passive-blind scheme for image forgery detection based on content-adaptive quantization table estimationIEEE Trans Circuits Syst Video Technol, 21
In the paper, we proposed a coarse-to-fine scheme to automatically detect the regions of interest (ROIs) for digitized cadastral images in Taiwan. To consider some issues such as the skew effect, image quality, and noise in digitized cadastral images, the proposed scheme is composed of four parts: pre-processing, skew correction, noise reduction, and ROI localization. In the pre-processing, each cadastral image is normalized and the prior knowledge is used to find the candidate region of the ROI. To reduce the impact of noise and poor contrast on line detection, an adaptive thresholding is adopted. To decrease the skew effect, the detected horizontal and vertical lines are analyzed to estimate the skew angle. After skew correction, an adaptive noise reduction algorithm is devised to reduce the effect of marginal, artificial, and random noise. The coordinates of the candidate region in the de-skew image with high resolution can be found and then the ROI boundary can be located correctly in the fine detection. Experimental results demonstrate that the proposed scheme can effectively and correctly localize ROIs in digitized cadastral images.
Multimedia Tools and Applications – Springer Journals
Published: Mar 20, 2017
Access the full text.
Sign up today, get DeepDyve free for 14 days.