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IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Detecting Femur Fractures by Texture Analysis of Trabeculae
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Automated detection of early lung cancer and tuberculosis based on X-ray image analysis
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Novel Approach to Pavement Cracking Automatic Detection Based on Segment Extending
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Automatic segmentation of femur bones in anterior-posterior pelvis x-ray images
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-organization for object extraction using a multilayer neural network and fuzziness measures
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Crack of the bone is a very serious medical condition. In medical applications, sensitivity in detecting medical problems and accuracy of detection are often in conflict. Computer detection of cracks can assist the doctors by flagging suspicious cases for closer examinations and thus improve the timeliness and accuracy. This paper presents the detailed image processing procedure including the grid formation, local thresholding, threshold value interpolation, segmentation using fuzzy index measure, background removal, and morphological filtering for the determination of infestation sites of a crack in X-ray image. The image processing procedure was tested with X-ray images of several types of crack bones. Additional tests and analyses were also performed using the developed algorithm on the X-ray images obtained with different image acquisition parameter. Compared to existing methods, this approach enhances the accuracy and reliability of proposed work.