Cutting Digital Images Using Curvelet Transform Millimeter

Abstract

Image fragmentation into non-overlapping areas where the boundaries contribute significantly in the utilization of the image in many areas of study like medical, imaging, and military technology. Curvelet transform method is used here due to its great possibilities and many advantages in preserving the borders of the image and its edges, in addition to its ability to capture information for these borders or soft edges in the image which helps draw the geography of territory and borders that contradict each other but within the limits of the overall picture. This research suggests the use of a normalized cut algorithm, which depends on fragmenting the selected image that was selected and converted using curvelet transform This provides a clear definition of the edges in the image and is cut into a number of sections required after calculating the eigenvalue and eigenvector by  divide The image to several sections required, the section to be studied in detail after being partially deducted from the original image identified and distinguished by the proposed algorithm the image which can give high-quality discrimination and accuracy, which is intended to this conclusion.