A sensing method for a counterfeit bill detector includes (i) using multiple image-sensing modules to scan multiple pieces of image information of a bill and converting the multiple pieces of image information into multiple values of digital image, (ii) comparing each value of digital image with a pre-stored image threshold value to generate a reference value, (iii) adding the multiple reference values to generate an image validation value, (iv) comparing the image validation value with a pre-stored validation threshold value to acquire a comparison result, and (v) determining if the multiple pieces of image information are valid according to the comparison result. The sensing method tackles the issue of unsynchronized actions in bill sensing and bill scanning and simultaneously eliminates the problem of distorted scanned bill image arising from entry of misaligned bill to improve accuracy in bill validation.

A character recognition method for recognizing a character printed over a background pattern on a valuable medium includes acquiring a character image captured by capturing the character printed on the valuable medium; evaluating a degree of similarity between the character image and each template image, the template image having been obtained beforehand by capturing each character that had a possibility of having been printed on the valuable medium and of which background area is evenly filled; and determining that the character corresponding to the template image showing the highest degree of similarity at the evaluating is the character included in the character image.

A method of generating handwriting information about handwriting of a user includes determining a first writing focus and a second writing focus; sequentially shooting a first local writing area, which is within a predetermined range from a first writing focus, and a second local writing area, which is within a predetermined range from a second writing focus; obtaining first handwriting from the first local writing area and second handwriting from the second local writing area; combining the first handwriting with the second handwriting; and generating the handwriting information, based on a result of the combining.

Systems and methods for shadow detection and reduction during document capture are disclosed herein. Temporary images of hardcopy documents are analyzed to determine the presence of a shadow or hotspot that obscures information of the hardcopy document. In response to detecting the shadow or hotspot, a controllable light source is used to illuminate the hardcopy document at predicted and/or predetermined intensities to minimize or eliminate the shadow on the hardcopy document. A permanent image of the hardcopy document illuminated by the controllable light source at the intensity that minimizes or eliminates the shadow is then stored. In this way, information of the hardcopy document (such as text, color, layout, spacing etc.) is increased in the permanent image and a need for post-processing the permanent image is reduced or eliminated.

A character segmenting apparatus may include a character segmenting position detecting unit to detect a segmenting position of characters. The character segmenting position detecting unit may include an area setting unit to set up an area for detecting the segmenting position; a projection creating unit configured to create a projection of pixel values, with respect to pixels arranged in a character placement direction, at least in a specified area set up by the area setting unit; a binarizing threshold value obtaining unit to calculate a moving average on the basis of minimum pixel values of the projection, in order to specify the moving average as a binarizing threshold value for the specified area; and a position detecting unit to calculate a character segmenting position on the basis of the binarizing threshold value.

A system and method select an image from multiple images taken at nearly the same time, based on blur, contour value or an estimate of either or both of these derived from the accelerometer of the device that captured the images, and then uploads the selected image.

A method, system, and machine-readable medium for classifying an image element as one of a plurality of categories, including assigning the image element based on a ratio between an unoccluded perimeter of the image element and an occluded perimeter of the image element and coding the image element according to a coding scheme associated with the category to which the image element is classified. Exemplary applications include image compression, where categories include image foreground and background layers.

A method, system, and machine-readable medium for classifying an image element as one of a plurality of categories, including assigning the image element based on a ratio between an unoccluded perimeter of the image element and an occluded perimeter of the image element and coding the image element according to a coding scheme associated with the category to which the image element is classified. Exemplary applications include image compression, where categories include image foreground and background layers.

A device, system, and method of detecting counterfeit articles are provided. The method includes receiving article identifying information associated with a test article, using the article identifying information to retrieve an authentic article image associated with the test article from an image storage database, scanning the test article to capture one or more images of the test article under different wavelength illuminations, and displaying the one or more test article images and the authentic article image to allow comparison of the test article and the associated authentic article. Additionally, multiple wavelength emitting elements may be located within an image-capturing device, to provide alternate illuminations of the test article, allowing alternating capture of images highlighting different security features for providing a superimposed image. A system of counterfeit article detection is also provided.

A method, system, and machine-readable medium for classifying an image element as one of a plurality of categories, including assigning the image element based on a ratio between an unoccluded perimeter of the image element and an occluded perimeter of the image element and coding the image element according to a coding scheme associated with the category to which the image element is classified. Exemplary applications include image compression, where categories include image foreground and background layers.