Abstract: Systems and methods for automatic processing of receipts to capture data from the receipts are presented. Upon receiving an image of a receipt, an optical character recognition (OCR) of the receipt content embodied in the image is executed. The OCR of the receipt content results in machine-encoded text content of the receipt content embodied in the image. Tokens are generated from the machine-encoded text content and data groups are constructed according to horizontal lines of generated tokens. Potential product items are identified for at least some of the constructed data groups and the potential product items are evaluated for the at least some constructed data groups. The evaluation of the potential product items for the at least some constructed data groups identifies receipt data, such as product items and vendor information, associated with the least some constructed data groups. The identified receipt data is captured and stored with the image of the receipt in a data store.

Abstract: Systems and methods for user-assisted processing of receipts to capture data from the receipts are presented. Upon receiving an image of a receipt, a receipt processing site processes the content of the receipt to identify potential product items. For those product items that would benefit from user assistance, sets of potential products items (each set corresponding to a particular area of the receipt image called an image box) are gathered and provided to the user in product item data. The product item data includes an image box for each set of potential product items. On a user computing device, a computer user evaluates the sets of potential product items and validates/clarifies the receipt content in view of the image boxes. Updated product item data is returned to the receipt processing site and the updated product data is used to update the product item information that the receipt processing site has generated regarding the received receipt.

Abstract: Systems and methods for automatic processing of receipts to capture data from the receipts are presented. Upon receiving an image of a receipt, an optical character recognition (OCR) of the receipt content embodied in the image is executed. The OCR of the receipt content results in machine-encoded text content of the receipt content embodied in the image. Tokens are generated from the machine-encoded text content and data groups are constructed according to horizontal lines of generated tokens. Potential product items are identified for at least some of the constructed data groups and the potential product items are evaluated for the at least some constructed data groups. The evaluation of the potential product items for the at least some constructed data groups identifies receipt data, such as product items and vendor information, associated with the least some constructed data groups. The identified receipt data is captured and stored with the image of the receipt in a data store.

Abstract: Systems, methods and computer-readable media are disclosed for capturing purchase information regarding purchased items of a consumer. Upon receiving an image of a receipt (a receipt image) regarding a list of purchased items, receipt text is generated. The receipt text is processed to identify the purchased items in the receipt image. Accordingly, an iteration is begun to iterate through the item blocks of the receipt text. An item block corresponds to a discrete item in the receipt text. The processing comprises extracting textual elements from the item block and matching the textual elements to a known product. Upon matching the textual elements to a known product, the consumer inventory associated with the consumer is updated with regard to the purchase of the known product.

Abstract: Systems, methods and computer-readable media are disclosed for capturing purchase information regarding purchased items of a consumer. Upon receiving an image of a receipt (a receipt image) regarding a list of purchased items, receipt text is generated. The receipt text is processed to identify the purchased items in the receipt image. Accordingly, an iteration is begun to iterate through the item blocks of the receipt text. An item block corresponds to a discrete item in the receipt text. The processing comprises extracting textual elements from the item block and matching the textual elements to a known product. Upon matching the textual elements to a known product, the consumer inventory associated with the consumer is updated with regard to the purchase of the known product.

Abstract: Systems, methods and computer-readable media are disclosed for capturing purchase information regarding purchased items of a consumer. Upon receiving an image of a receipt (a receipt image) regarding a list of purchased items, receipt text is generated. The receipt text is processed to identify the purchased items in the receipt image. Accordingly, an iteration is begun to iterate through the item blocks of the receipt text. An item block corresponds to a discrete item in the receipt text. The processing comprises extracting textual elements from the item block and matching the textual elements to a known product. Upon matching the textual elements to a known product, the consumer inventory associated with the consumer is updated with regard to the purchase of the known product.