36844 results about "Image based" patented technology

A digital-imaging based system for and method of reading graphical indicia, including code symbols, on objects such as, but not limited to, code symbol menus by the user simply pointing his or her finger at the particular code symbol on the code symbol menu to be read, while digital images of the code symbol menu and the pointing finger are automatically captured, buffered and processed.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

A computer implemented method of creating a dental model for use in dental articulation includes providing a first set of digital data corresponding to an upper arch image of at least a portion of an upper dental arch of a patient, providing a second set of digital data corresponding to a lower arch image of at least a portion of a lower dental arch of the patient, and providing hinge axis data representative of the spatial orientation of at least one of the upper and lower dental arches relative to a condylar axis of the patient. A reference hinge axis is created relative to the upper and lower arch images based on the hinge axis data. Further, the method may include bite alignment data for use in aligning the lower and upper arch images. Yet further, the method may include providing data associated with condyle geometry of the patient, so as to provide limitations on the movement of at least the lower arch image when the arch images are displayed. Further, a wobbling technique may be used to determine an occlusal position of the lower and upper dental arches. Various computer implemented methods of dental articulation are also described. For example, such dental articulation methods may include moving at least one of the upper and lower arch images to simulate relative movement of one of the upper and lower dental arches of the patient, may include displaying another image with the upper and lower dental arches of the dental articulation model, and / or may include playing back recorded motion of a patient's mandible using the dental articulation model.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

In a system and method for the generation of attack-resistant, user-friendly, image-based CAPTCHAs (Completely Automated Public test to Tell Computers and Humans Apart), controlled distortions are applied to randomly chosen images and presented to a user for annotation from a given list of words. An image is presented that contains multiple connected but independent images with the borders between them distorted or otherwise visually obfuscated in a way that a computer cannot distinguish the borders and a user selects near the center of one of the images. The distortions are performed in a way that satisfies the incongruous requirements of low perceptual degradation and high resistance to attack by content-based image retrieval systems. Word choices are carefully generated to avoid ambiguity as well as to avoid attacks based on the choices themselves.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.