Removing Noise Dots Points from the Scanning various Images using Epipolar Geometry with Matlab

In this paper, we explore possibilities to improve quality images by using Epipolar geometry with mat lab. The source images can give best results with the best clarity pixel to pixel achievement. The goal is make character segmentation results more reduce the need image for user interaction with the help of Epipolar geometry. We clean up isolated noise dots without removing small dots that are parts of characters. The system has been tested with real camera images or satellite images under various character conditions. We discover a set of high geometric and appearance constraints with low level the images matches' reliable matching results. We use lines because they have some advantages with respect to points, particularly in manmade environments. We cleaned dots on images estimating thresholding simultaneously with transformation method. We are closely trying to solve Mat lab scripts to clean up scanned pages from old manuscripts. To find particular character with clean noise dots from the image database sources.

[1]  Domenico Prattichizzo,et al.  Keeping features in the field of view in eye-in-hand visual servoing: a switching approach , 2004, IEEE Transactions on Robotics.

[2]  Richard I. Hartley,et al.  In defence of the 8-point algorithm , 1995, Proceedings of IEEE International Conference on Computer Vision.

[3]  Hayder Radha,et al.  Image compression using binary space partitioning trees , 1996, IEEE Trans. Image Process..

[4]  Jake K. Aggarwal,et al.  On the computation of motion from sequences of images-A review , 1988, Proc. IEEE.

[5]  K. Muller,et al.  Symbolic Description of Intracerebral Vessels Segmented from MRA and Evaluation by Comparison with X-Ray Angiograms , 2000 .

[6]  Richard I. Hartley,et al.  Theory and Practice of Projective Rectification , 1999, International Journal of Computer Vision.

[7]  Hiroshi Nakanishi,et al.  Traffic Flow Measuring System Using Image Processing , 1990, Other Conferences.

[8]  A. Verri,et al.  A compact algorithm for rectification of stereo pairs , 2000 .

[9]  Guoping Qiu,et al.  Color image coding, indexing and retrieval using binary space partitioning tree , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[10]  Thomas A. Dingus,et al.  Evaluating New Technologies to Enhance Night Vision by Looking at Detection and Recognition Distances of Non-Motorists and Objects , 2001 .

[11]  Shree K. Nayar,et al.  Rectifying transformations that minimize resampling effects , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[12]  Stephen R. Aylward,et al.  Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction , 2002, IEEE Transactions on Medical Imaging.

[13]  USING EPIPOLAR GEOMETRY APPLYING THE BIT-PLANE ON IMAGES USING MAT LAB , 2012 .

[14]  Vijayan K. Asari,et al.  A Visibility Improvement System for Low Vision Drivers by Nonlinear Enhancement of Fused Visible and Infrared Video , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[15]  Emanuele Trucco,et al.  Projective rectification without epipolar geometry , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[16]  Stephen R. Aylward,et al.  Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparison with X-ray angiograms , 2001, Medical Image Anal..

[17]  Salvatore A. D Agostino.  Commercial machine vision system for traffic monitoring and control , 1992 .

[18]  Vijayan K. Asari,et al.  A multisensor image fusion and enhancement system for assisting drivers in poor lighting conditions , 2005, 34th Applied Imagery and Pattern Recognition Workshop (AIPR'05).

[19]  J. Bärgman,et al.  Pedestrian Detection with near and far Infrared Night Vision Enhancement , 2007 .

[20]  Antonio Bicchi,et al.  Vision-based dynamic estimation and set-point stabilization of nonholonomic vehicles , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).