Automatic detection of fractures from IR images is considered as an important process in medical image analysis by both orthopedic and radiologic point of view. X-Ray is one of the oldest and frequently used devices, as they are non-invasive, painless and economical. A bone x-ray makes images of any bone in the body and a typical bone ailment is the fracture, which are cracks in bones. Detection and correct treatment of fractures are considered important, as a wrong diagnosis often lead to ineffective patient management, increased dissatisfaction and expensive litigation. This paper proposes a fusion-classification technique for automatic fracture detection from bones, in particular the hand bones. The proposed system has four steps, namely, preprocessing, segmentation, feature extraction and bone detection, which use an amalgamation of image processing techniques for successful detection of fractures. The results from various experiments prove that the proposed system is shows significant improvement in terms of detection rate and speed of classification.
[1]
Soumen Kanrar,et al.
Enhancement of Image Resolution by Binarization
,
2010,
ArXiv.
[2]
Mukesh Sharma,et al.
A Method for Binary Image Thinning using Gradient and Watershed Algorithm
,
2013
.
[3]
Réjean Plamondon,et al.
Automatic signature verification and writer identification - the state of the art
,
1989,
Pattern Recognit..
[4]
R. C. Thomas,et al.
Computer Vision: A First Course
,
1988
.
[5]
Dr. A. Damodaram,et al.
INNOVATIVE THINNING AND GRADIENT ALGORITHM FOR EDGE FIELD AND CATEGORIZATION SKELETON ANALYSIS OF BINARY AND GREY TONE IMAGES
,
2009
.
[6]
Anil K. Jain.
Fundamentals of Digital Image Processing
,
2018,
Control of Color Imaging Systems.
[7]
T. W. Ridler,et al.
Picture thresholding using an iterative selection method.
,
1978
.