Provided is an image processing apparatus including an acquisition unit configured to acquire a multi-valued image and a binarization unit configured to generate a binary image obtained by binarizing the multi-valued image, and the stated image processing apparatus is configured such that the binarization unit detects a closed region within the multi-valued image, and binarizes the inside of the closed region based on luminance inside the closed region and luminance around the closed region.

Systems and methods for using a mobile device to submit an application for an insurance policy using images of documents captured by the mobile device are provided herein. The information is then used by an insurance company to generate a quote which is then displayed to the user on the mobile device. A user captures images of one or more documents containing information needed to complete an insurance application, after which the information on the documents is extracted and sent to the insurance company where a quote for the insurance policy can be developed. The quote can then be transmitted back to the user. Applications on the mobile device are configured to capture images of the documents needed for an insurance application, such as a driver's license, insurance information card or a vehicle identification number (VIN). The images are then processed to extract the information needed for the insurance application.

A method and apparatus for extraction of dots in an image are described. An image is binarized according to an initial intensity threshold to obtain an initial binary image including foreground and background pixels. Each foreground pixel has a foreground intensity value and each background pixel has a background intensity value. A set of blobs including foreground pixels is selected from the initial binary image to be part of a selected set of dots, where each blob from the set of blobs has characteristics of a dot. Responsive to determining that a successive binarization is to be performed, the following operations are repeated: (1) binarization of the image according to a successive intensity threshold (2) selection of a successive set of blobs, where each blob has characteristics of a dot. Responsive to determining that a successive binarization is not to be performed, the selected set of dots is output.

There is provided an image processing apparatus in which a part used in predetermined processing is specified with use of a relatively small binarization threshold, from parts that have been converted into black pixels through binarization processing using a relatively large binarization threshold.

A document type recognition apparatus includes an image region separation unit, a smoothing unit, an edge enhancement unit, a histogram creation unit, and a document type recognition unit. The image region separation unit outputs a signal indicative of each region obtained by separating an input image into a character region and a pattern region. The smoothing unit performs smoothing processing to remove halftone dots of a particular number of lines or greater in the pattern region of the input image. The edge enhancement unit outputs an image subjected to edge enhancement processing depending on an amount of edge on an edge portion of the character region in the input image subjected to the smoothing processing. The histogram creation unit creates a histogram of the image subjected to the edge enhancement processing. The document type recognition unit recognizes a document type of the input image by utilizing the histogram.

Systems and methods are provided for processing and extracting content from an image captured using a mobile device. In one embodiment, an image is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by adjusting the image, identifying the format and layout of the document, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image adjusting may be implemented to accurately assess features of the document, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

A comprising: processing the image to a text image with a number of text blobs; classifying the text blobs based on a calculation as to whether they will belong to a foreground layer or to a background layer in OCR processing; and generating a quality value of the image based on the classified text blobs. By generating the quality value based on the classified text blobs, pictures in the image, which are not relevant for OCR are not taken into account for assessing the quality of the image. The amount of data to be processed is thereby decreased resulting in a method which can be executed in real-time. Furthermore, as the quality assessment criterion is based on the division of blobs into a foreground and a background layer, i.e. on prior knowledge of the OCR system, it provides a good indication for OCR accuracy.

Techniques for processing images of documents captured using a mobile device are provided. The images can include different sides of a document from a mobile device for an authenticated transaction. In an example implementation, a method includes inspecting the images to detect a feature associated with a first side of the document. In response to determining an image is the first side of the document, a type of content is selected to be analyze on the image of the first side and one or more of regions of interests (ROIs) are identified on the image of the first side that are known to include the selected type of content. A process can include receiving a sub-image of the image of the first side from the preprocessing unit, and performing content detection test on the sub-image.

A method of detecting a dot code includes: irradiating the dot code and a background surface by a source of radiation capturing by a reader an image of the dot code and the background surface; distinguishing in the image an edge surface from the background surface based on the difference in spectral reflectivity of the edge surface and the background surface; processing the image of the dot code by dilating in the image the edge surface of the dot, until the centre surface has been closed by the dilating; and reading the processed image to derive the dot code from the processed image. An item includes the dot code having a plural dots arranged on the background surface, where a spectral reflectivity of the edge surface differs from a spectral reflectivity of the background surface.

A method of detecting a dot code includes: irradiating the dot code and a background surface by a source of radiation capturing by a reader an image of the dot code and the background surface; distinguishing in the image an edge surface from the background surface based on the difference in spectral reflectivity of the edge surface and the background surface; processing the image of the dot code by dilating in the image the edge surface of the dot, until the centre surface has been closed by the dilating; and reading the processed image to derive the dot code from the processed image. An item includes the dot code having a plural dots arranged on the background surface, where a spectral reflectivity of the edge surface differs from a spectral reflectivity of the background surface.