Abstract: The present specification discloses methods for scanning objects for the presence of lithium batteries. Normalized transmission X-ray data is used to generate organic, effective Z, and attenuation-based images. These images are then segmented using a combination of thresholding and region growing techniques to identify regions of interest. The regions are classified as lithium batteries or other objects, based on characteristics such as area of the region, its organic intensity, Zeff number, shape, spatial arrangement and texture.

Abstract: The present specification discloses methods for scanning objects for the presence of lithium batteries. Normalized transmission X-ray data is used to generate organic, effective Z, and attenuation-based images. These images are then segmented using a combination of thresholding and region growing techniques to identify regions of interest. The regions are classified as lithium batteries or other objects, based on characteristics such as area of the region, its organic intensity, Zeff number, shape, spatial arrangement and texture.

Abstract: The present specification discloses methods for scanning objects for the presence of lithium batteries. Normalized transmission X-ray data is used to generate organic, effective Z, and attenuation-based images. These images are then segmented using a combination of thresholding and region growing techniques to identify regions of interest. The regions are classified as lithium batteries or other objects, based on characteristics such as area of the region, its organic intensity, Zeff number, shape, spatial arrangement and texture.

Abstract: The present specification discloses methods for scanning objects for the presence of lithium batteries. Normalized transmission X-ray data is used to generate organic, effective Z, and attenuation-based images. These images are then segmented using a combination of thresholding and region growing techniques to identify regions of interest. The regions are classified as lithium batteries or other objects, based on characteristics such as area of the region, its organic intensity, Zeff number, shape, spatial arrangement and texture.

Abstract: In some aspects, the disclosure is directed methods and systems for constructing a three dimensional (3D) color representation of an object. A first sensor may acquire a first depth image and a first color image of an object from a first angle relative to the object. A second sensor may acquire a second depth image and a second color image of the object from a second angle relative to the object. A processor may map color information from pixels of the first color image to pixels of the first depth image to form a first 3D distribution of colored points representing a first surface portion of the object. The processor may map color information from pixels of the second color image to pixels of the second depth image to form a second 3D distribution of colored points representing a second surface portion of the object. The processor may match, based on 3D structure, a portion of the first 3D distribution of colored points, to a portion of the second 3D distribution of colored points.