X - Ray Image Analysis in Identification of Bone Cancer Using Laws Features and Machine Learning Model

The human bone is significantly controlled by the humanoid system. The strange development and fragmentation of unit in bone prompts a bone tumor, and further development of bone growth prompts to bone disease. Generally, Image processing plays the vital role than lessens human judgment that provides exact outcomes. Our paper aims to specialize in the utilization of various strategies for the revelation of bone malignant growth in X-RAY images. In this study, bilateral filter (BF) is used as a pre-processing tool to reduce and smooth out noise. Segmentation is achieved by adaptive histogram followed by binary thresholding and well-founded location of the desired region. Statistical and Laws features are used to train the Support Vector Machine (SVM). The resultant result will be reviewed through different execution measures that incorporate accuracy, sensitivity and specificity.