Here we proposed an automated techniques and methods to detect fracture. X-ray images are examined manually but it is time consuming and prone to errors. As X-ray images are more suspected to noise we used many preprocessing steps to remove noise and blur from image. Thus, system is able to detect fracture more accurately. System detects fracture based on the type of fracture. Noise is removed from the image and image is transformed to clearer image so that system can easily detect fracture. We used image processing methodology to track bone. All unwanted as well as smaller objects are removed by the system. Finally based on the connected component, system detects fracture. System displays bounding box around the fracture. This system involves image preprocessing steps and fracture detection based on type of fracture. The proposed system is able to detect bone dislocation with 80% success rate and bone major fracture 60-70% accuracy and minor fracture with 50-60% accuracy. |
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