Abstract: A bulk loading system for delivering bulk material to a storage compartment of a bulk transport vehicle through a hatch opening includes a movable positioner supporting an extendable loading spout assembly, a camera coupled to the positioner and a programmable logic controller communicatively coupled to the positioner, loading spout assembly and camera for automatically positioning the loading spout assembly over the hatch opening and filling the storage compartment of the vehicle with bulk material. The system provides accurate position information to a driver of the vehicle so that the vehicle and its storage compartments can be quickly positioned within a reach zone of the loading spout.

Abstract: The application belongs to the field of big data, and particularly relates to an official document processing method, device, computer equipment and storage medium. The method includes the following steps of: performing format analysis on the to-be-reviewed official document, then acquiring the to-be-reviewed official document of standard file type, and identifying all file components and contents in the to-be-reviewed official document of standard file type; performing text format detection, text content detection and frame layout detection synchronously by a preset text processing model, obtaining a format detection result, a content detection result and a layout detection result; generating a detected error content according to the format detection result, content detection result and layout detection result, calling out a standard writing rule corresponding to the detected error content, marking the detected error content and the standard writing rule in the to-be-reviewed official document.

Abstract: Distinguishing pattern differences from non-pattern differences. A set of differences is identified. The set comprises a plurality of differences between first and second versions of a document. A pattern is identified. The pattern explains a transformation from a first string in the first version of the document to a second string in the second version of the document. A subset of differences are identified. The subset comprises a plurality of differences, from among the set, which match the pattern. While presenting a user interface that visually highlights differences between the first and second versions of the document, a first visual treatment is applied to a first difference, based on the first difference being included in the subset. A second visual treatment is also applied to a second difference, based on the second difference being excluded from the subset. The second visual treatment is different than the first visual treatment.

Abstract: Systems and methods for registering arbitrary visual features for use as fiducial elements are disclosed. An example method includes aligning a geometric reference object and a visual feature and capturing an image of the reference object and feature. The method also includes identifying, in the image of the object and the visual feature, a set of at least four non-colinear feature points in the visual feature. The method also includes deriving, from the image, a coordinate system using the geometric object. The method also comprises providing a set of measures to each of the points in the set of at least four non-colinear feature points using the coordinate system. The measures can then be saved in a memory to represent the registered visual feature and serve as the basis for using the registered visual feature as a fiducial element.

Abstract: A system for detecting scan and non-scan events in a self-check out (SCO) process includes a a scanner for scanning objects and generating point of sale (POS) data, a video camera for generating a video of the scanning region, proximity sensors proximal to the video camera for defining an Area of Action (AoA), wherein the video camera starts capturing scanning region, when the objects enter the AoA, and the POS data includes non-zero values, an Artificial neural network (ANN) for receiving an image frame and generating one or more values, each indicating a probability of classification of the image frame into one or more classes respectively, and a processing unit for processing the POS data, and probabilities of one or more classes to detect a correlation between video data and POS data, and detect one of: scan and non-scan event in the image frame based on the correlation.

Abstract: A system receives a record which includes a string and separates the string into a number of tokens, including a token and another token. The system identifies a pattern that includes an entity, another entity, and a number of entities that equals the number of tokens, and another pattern that includes the same number of entities as the number of tokens. The system determines a combined probability that combines a probability based on the number of entries in the entity's dictionary which stores the token, and another probability based on a number of character types in the other entity that match characters in the other token. If the combined probability associated with the pattern is greater than another combined probability associated with the other pattern, the system matches the record to a system record based on recognizing the token as the entity and the other token as the other entity.

Abstract: A method and a system for producing a story video are provided. A method for producing a story video, according to one embodiment, can produce a specific story video by determining a theme of a story that is suitable for collected videos and selecting and arranging an appropriate video for each frame of a template associated with the theme.

Abstract: Aspects of the subject disclosure may include, for example, embodiments include obtaining video content, the video content comprises a plurality of frames, monitoring, by an image sensor, a facial feature of a user to determine a visual focus of the user in relation to the video content, and detecting from a group of frames of the plurality of frames at least a reduction in movements of objects in the group of frames. Further embodiments include determining, according to the monitoring and the detecting, a measure of attention of the user within a region of the group of frames, determining that the measure of attention of the user within the region of the group of frames satisfies a threshold, and embedding in at least a portion of subsequent frames of the plurality of frames a visual advertisement in the region via a communication device. Other embodiments are disclosed.

Abstract: One embodiment includes a computer-implemented data labeling platform. The platform provides a confidence-driven workflow (CDW) executable to receive and process labeling requests to label data items. The CDW comprises a set of executable labelers, each labeler in having a dynamically modeled confidence range. The execution path for processing a labeling request to label a data item is dynamically determined.

Abstract: Methods and apparatus of Exclusive OR (XOR) engine in a random access memory device to accelerate cryptographical operations in processors. For example, an integrated circuit memory device enclosed within a single integrated circuit package can include an XOR engine that is coupled with memory units in the random access memory device (e.g., having dynamic random access memory (DRAM) or non-volatile random access memory (NVRAM)). A processor (e.g., System-on-Chip (SoC) or Central Processing Unit (CPU)) can have encryption logic that performs cryptographical operations using XOR operations that are performed by the XOR engine in the random access memory device using the data in the random access memory device.

Abstract: Methods, systems, and articles of manufacture to improve image recognition searching are disclosed. In some embodiments, a first document image of a known object is used to generate one or more other document images of the same object by applying one or more techniques for synthetically generating images. The synthetically generated images correspond to different variations in conditions under which a potential query image might be captured. Extracted features from an initial image of a known object and features extracted from the one or more synthetically generated images are stored, along with their locations, as part of a common model of the known object. In other embodiments, image recognition search effectiveness is improved by transforming the location of features of multiple images of a same known object into a common coordinate system. This can enhance the accuracy of certain aspects of existing image search/recognition techniques including, for example, geometric verification.

Abstract: Provided is an information acquisition system including: an image capture apparatus including a camera that captures a target object to generate an image; and a control apparatus including a control unit that controls the image capture apparatus so that a plurality of images in accordance with a plurality of different environment conditions are generated and an information acquisition unit that acquires target object information input to a discriminator that identifies an object, in which the target object information includes the plurality of images or a plurality of feature amounts obtained from the plurality of images.

Abstract: There is provided an image processing apparatus that performs noise reduction processing by using a patch obtained by dividing an image into small areas. The image processing apparatus includes a setting unit configured to set, for the image, a patch of interest, a search unit configured to search the image for a similar patch based on the patch of interest, a generation unit configured to generate one or more synthesis patches different from a patch included in the image, based on at least one of the patch of interest and the similar patch, and a noise reduction unit configured to reduce noise in the patch of interest by using a patch group including the patch of interest, the similar patch, and the one or more synthesis patches.

Abstract: There is provided with an image processing apparatus. A focused patch setting unit sets a focused patch in an input image. The focused patch has a first number of pixels. A detecting unit detects a plurality of similar patches that are similar to the focused patch in the input image. A target patch setting unit sets, based on the plurality of similar patches, a plurality of target patches including at least one pixel included in the similar patch and having a second number of pixels that is different from the first number of pixels. A noise reduction processing unit performs, based on the plurality of target patches, a noise reduction process on the target patches. A merging unit merges the target patches whose noise has been reduced by the noise reduction processing unit to generate an output image.

Abstract: A bulk loading system for delivering bulk material to a storage compartment of a bulk transport vehicle through a hatch opening includes a movable positioner supporting an extendable loading spout assembly, a camera coupled to the positioner and a programmable logic controller communicatively coupled to the positioner, loading spout assembly and camera for automatically positioning the loading spout assembly over the hatch opening and filling the storage compartment of the vehicle with bulk material. The system provides accurate position information to a driver of the vehicle so that the vehicle and its storage compartments can be quickly positioned within a reach zone of the loading spout.

Abstract: A system and method for matching a pattern may include generating a set of model descriptors representative of segment features of a first imaged object. A set of query descriptors representative of segment features of a second imaged object may be generated. A first model segment may be selected to align with the query segments to determine if any of the query segments correspond with the first model segment based on respective model descriptors and query descriptors. An hypothesis may be generated by computing a transformation to match the selected first model descriptor with a query descriptor. The hypothesis may be validated by a model fitting algorithm when comparing other transformed model descriptors with other query descriptors. Based on a consensus value from the model fitting algorithm, a determination as to whether a pattern match exists between the first and second images may be made.

Abstract: According to one embodiment, managing a plurality of variable data templates can comprise cataloging, by a template management system, each of the variable data templates according to a shape criteria. The shape criteria of each variable data template can be based on a size and location of one or more variable data fields defined in the template. The cataloged variable data templates can be classified into one or more shape families based on the shape criteria of each variable data template. The template management system can detect a request to locate a variable data template and search the plurality of variable data templates for one or more suggested variable data templates having the shape criteria matching the template. An indication of the suggested variable data templates can be provided by the template management system.

Abstract: Systems and methods for registering arbitrary visual features for use as fiducial elements are disclosed. An example method includes aligning a geometric reference object and a visual feature and capturing an image of the reference object and feature. The method also includes identifying, in the image of the object and the visual feature, a set of at least four non-colinear feature points in the visual feature. The method also includes deriving, from the image, a coordinate system using the geometric object. The method also comprises providing a set of measures to each of the points in the set of at least four non-colinear feature points using the coordinate system. The measures can then be saved in a memory to represent the registered visual feature and serve as the basis for using the registered visual feature as a fiducial element.

Abstract: A method for use in an associative memory device when multiplying by a sparse matrix includes storing only non-zero elements of the sparse matrix in the associative memory device as multiplicands. The storing includes locating the non-zero elements in computation columns of the associative memory device according to linear algebra rules along with their associated multiplicands such that a multiplicand and a multiplier of each multiplication operation to be performed are stored in a same computation column. The locating locates one of the non-zero elements in more than one computation column if one of the non-zero elements is utilized in more than one multiplication operation.

Abstract: The disclosure herein generally relate to scene change detection, and, more particularly, to use of Unmanned Vehicle (UV) to inspect a scene and perform a scene change detection using UVs. When a UV performs visual inspection of an area or an object, due to various factors, such as but not limited to environmental factors, and movement of object and/or the UV, image of the area/object captured by the drone lacks clarity, which in turn makes detection of any object a difficult task. The UV disclosed herein uses a multi scale super pixel technique for visual change detection, in order to solve the aforementioned issues. In an embodiment, the UV captures an image, identifies a reference image that matches the captured image, and generates a change map. The multi-scale super pixel analysis is then performed on this change map to detect changes between the captured image and the reference image.

Abstract: An image processing apparatus includes a still image data creation unit and a still image data extraction unit. The still image data extraction unit calculates a first feature value of the sampling target still image data, determines whether the sampling target still image data is first extraction target still image data as an extraction target based on the first feature value, and calculates a second feature value of adjacent still image data. The adjacent still image data are a plurality of still image data in a range preset in time series of the first extraction target still image data. The still image data extraction unit determines whether the adjacent still image data is second extraction target still image data as an extraction target or not based on the second feature value and extracts the first extraction target still image data and the second extraction target still image data.

Abstract: A method for inspecting a vehicle includes acquiring a unique identity number of an insepected vehicle, carrying out X-ray scanning on the inspected vehicle to acquire an X-ray image of the inspected vehicle, retrieving at least one historical inspected image related to the unique identity number from a historical inspection database, determining, based on one template image selection algorithm selected from multiple template image selection algorithms, one of the at least one historical inspected images as a template image, determining a difference region between the X-ray image and the template image, and presenting the difference region to a user.

Abstract: According to one aspect of the present disclosure a method and technique for managing data transfer is disclosed. The method includes comparing, by a processor unit of a data processing system, data to be written to a memory subsystem to a stored data pattern and, responsive to determining that the data matches the stored data pattern, replacing the matching data with a pattern tag corresponding to the matching data pattern. The method also includes transmitting the pattern tag to the memory subsystem.

Abstract: In accordance with one embodiment, an intelligent video thumbnail selection and generation tool may select a relevant and visually stimulating image from a video file and generate a thumbnail including the image. The image may be selected by computing a relevancy metric for an image in the file based on one or more selected relevant features, and comparing that relevancy metric with the metric of at least one other image in the file. In another embodiment, a series of images in a video file may be divided into shots. One of the shots may be selected based on a shot relevancy metric and a key image from the shot may be selected as a thumbnail based on a key image relevancy metric, where the shot relevancy metric and the key image relevancy metrics may be computed based on one or more relevant content features.

Abstract: According to an embodiment, a device includes a detector, first and second recognizers, an estimator, a second recognizer, and an output unit. The detector is configured to detect a visible text area including a visible character from an image. The first recognizer is configured to perform character pattern recognition on the visible text area, and calculate a recognition cost according to a likelihood of a character pattern. The estimator is configured to estimate a partially-hidden text area into which a hidden text area estimated to have a hidden character and the visible text area are integrated. The second recognizer is configured to calculate an integrated cost into which the calculated cost and a linguistic cost corresponding to a linguistic likelihood of a text that fits in the entire partially-hidden text area are integrated. The output unit is configured to output a text selected or ranked based on the integrated cost.

Abstract: A remote-camera control method includes: obtaining first remote image data and terminal image data acquired by photography performed by a remote camera and a terminal camera in a same time segment; authenticating the user terminal by comparing the two pieces of image data with each other and by determining that the user terminal is in a photography spot of the remote camera when an identical subject is found in both the pieces of image data; and providing second remote image data acquired by the remote camera to the user terminal after the user terminal is authenticated.

Abstract: A method of measuring customer satisfaction with a product. The method may assess customer satisfaction from information collected after purchasing the product. This post-purchase information may be collected, for example, by monitoring customer expressions made while interacting with the product. Optionally, the settings and operating conditions of the product may be separately monitored and cross-referenced with the customer expressions to tie the expressions with specific characteristics of the product.

Abstract: In accordance with one embodiment, an intelligent video thumbnail selection and generation tool may select a relevant and visually stimulating image from a video file and generate a thumbnail including the image. The image may be selected by computing a relevancy metric for an image in the file based on one or more selected relevant features, and comparing that relevancy metric with the metric of at least one other image in the file. In another embodiment, a series of images in a video file may be divided into shots. One of the shots may be selected based on a shot relevancy metric and a key image from the shot may be selected as a thumbnail based on a key image relevancy metric, where the shot relevancy metric and the key image relevancy metrics may be computed based on one or more relevant content features.

Abstract: A client (1) is provisioned with a content selection unit (13) for referencing description information (26), selecting content to be played in a certain period, and at the same time, and selecting content to be played at the next period from an id of a subset that is the same as the subset selected at the period, a request execution unit (14) for requesting the transmission of the selected content, and a content playback unit (15) for continuously playing the content transmitted in response to the request.

Abstract: To generate a description of a raster map image that includes a representation of a body of water having a color gradient that appears constant in response to a zoom operation, a description of geometry of the body of water is generated for a selected geographic area. Using a raster representation of the body of water having a color gradient, at least two blur raster images are generated: a first blur raster image is generated using a first blur radius, and a second blur raster image is generated using a second blur radius different from the first blur radius. The description of the geometry of the body of water, the first blur raster image, and the second blur raster image are provided to a client device for generating raster map images of the selected geographic area.

Abstract: An image processing device, method, computer readable storage medium, and image forming device that calculate spatial frequency of input image data and determine a frequency component in which a distribution amount of the spatial frequency maximizes, and perform an enhancement process by applying, to the input image data, an enhancement amount that varies according to the distribution amount of the spatial frequency, based on the determined frequency component.

Abstract: In one embodiment, dividing a set of texts into one or more text blocks, each text block including a portion of the set of texts; rendering each text block to obtain one or more rendered text blocks; determining a placement instruction for each rendered text block, the placement instruction indicating a position of the rendered text block when it is displayed; and sending the one or more rendered text blocks and their respectively associated placement instructions to a electronic device for displaying on the electronic device.

Abstract: Embodiments of the invention relate to reducing memory required to store an array of formulas and values corresponding to a formula-array. A set of formula-array representations is provided and arranged in a successive order. Each formula-array representation is evaluated for an associated memory requirement to support use thereof, followed by conversion to a structure of the formula-array representation at a successive level. Selection of the formula-array representation is determined based upon a minimal memory requirement from the formula-array representations in the order.

Abstract: The invention pertains to a method for segmenting an image from a sequence of video images into a foreground and a background, the image being composed of pixels, the method includes assigning an initial foreground probability to each of the pixels; assigning a set of probability propagation coefficients to each of the pixels; and applying a global optimizer to the initial foreground probabilities of the pixels to classify each of the pixels as a foreground pixel or a background pixel, to obtain a definitive foreground map; wherein the global optimizer classifies each processed pixel in function of the initial foreground probability of the processed pixel and the initial foreground probability of neighboring pixels, the relative weight of the initial foreground probability of neighboring pixels being determined by the probability propagation coefficients of the neighboring pixels.

Abstract: In techniques for fast dense patch search and quantization, partition center patches are determined for partitions of example image patches. Patch groups of an image each include similar image patches and a reference image patch that represents a respective patch group. A partition center patch of the partitions is determined as a nearest neighbor to the reference image patch of a patch group. The partition center patch can be determined based on a single-nearest neighbor (1-NN) distance determination, and the determined partition center patch is allocated as the nearest neighbor to the similar image patches in the patch group. Alternatively, a group of nearby partition center patches are determined as the nearest neighbors to the reference image patch based on a k-nearest neighbor (k-NN) distance determination, and the nearest neighbor to each of the similar image patches in the patch group is determined from the nearby partition center patches.

Abstract: According to an embodiment, a searching device includes an acquiring unit, a receiver, a calculator, and a determining unit. The acquiring unit is configured to acquire a first image. The receiver is configured to receive selection of a first area contained in the first image. The calculator is configured to calculate, for each of a plurality of second images to be searched, a first similarity with the first area and a second similarity with a second area that has been received by the receiver before the first area. The determining unit is configured to determine a third image or third images to be presented from among the second images on the basis of a result of a logical operation of the first similarity and the second similarity for each of the second images.

Abstract: Respective models of visual weight in images are determined. An image query is generated from a determined visual weight distribution. At least one of the images is retrieved from a database based on comparisons of the image query with respective ones of the visual weight models.

Abstract: Provided are image processing method and apparatus. The method includes selecting one of a plurality of images matched in structure as reference image, and select another of the images as subject image; for a subject pixel in the subject image, determining a pixel corresponding to the subject pixel in the reference image; calculating similarity values of at least part of pixels in the reference image with respect to the pixel corresponding to the subject pixel; establishing weight coefficients based on the similarity values, and weighted averaging the subject pixel in the subject image to obtain a processed pixel value. With the above solutions, it is possible to use structure information of a higher-quality image in processing another image, and thus improve quality of the other image.

Abstract: Disclosed is an image creating device including a first obtaining unit which obtains an image including a face, a first extraction unit which extracts a face component image relating to main components of the face in the image and a direction of the face, a second obtaining unit which obtains a face contour image associated to the face in the image and a second extraction unit which extracts a direction of a face contour in the face contour image. The image creating device further includes a converting unit which converts at least one of the face component image and the face contour image based on the both directions of the face and the face contour and a creating unit which creates a portrait image by using at least one of the face component image and the face contour image being converted by the converting unit.

Abstract: The invention is related to a method of matching image features with reference features, comprising the steps of providing a current image captured by a capturing device, providing reference features (r), wherein each of the reference features comprises at least one reference feature descriptor (d(r)), determining current features (c) in the current image and associating with each of the current features at least one respective current feature descriptor (d(c)), and matching the current features with at least some of the reference features by determining a respective similarity measure (D(c, r)) between each respective current feature descriptor (d(c)) and each respective reference feature descriptor (d(r)). According to the invention, the determination of the similarity measure is performed on an integrated circuit by hardwired logic or configurable logic which processes logical functions for determining the similarity measure.

Abstract: An image similarity determining device and method and an image feature acquiring device and method are provided. The image similarity determining device comprises a preprocessing unit for extracting feature points of each input image region of an input image and each image region to be matched of a data source image; a matched feature point set determining unit for determining one to one matched feature point pairs between input image regions and image regions to be matched to determine matched feature point sets; a geometry similarity determining unit for determining a geometry similarity between the input image region and the image region to be matched based on distribution of respective feature points in the matched feature point sets; and an image similarity determining unit for determining similarity between input image and data source image based on geometry similarities between input image regions and corresponding image regions to be matched.

Abstract: An image processing method includes searching for areas matching each other between a plurality of input images, the plurality of input images comprising a reference image and a target image, generating hierarchical image structures formed of a plurality of hierarchical images having different resolutions with respect to the matching areas between the plurality of input images, repeatedly performing image processing based on a similarity of values of pixels matching each other in the plurality of hierarchical images of the same level by using the hierarchical image structures generated with respect to the matching areas, and generating an output image by using pixel values according to the repeated image processing.

Abstract: A method and system for calculating oblong-shape rotation angles from optical image data of arbitrary size for user interface applications is described without the need of eigenvector routines and storage of the image data. The oblong shape may be of arbitrary size and location and need not be precisely elliptical. A few running sums are calculated and stored throughout each scan, and the results are obtained in closed form by simple post-scan computation. An algorithmic embodiment can execute on one or more hardware processors with limited or otherwise constrained computation power, available instruction cycles, available memory, etc. Hardware processors may CPUs found in desktops, laptops, tablets, or handheld computing devices. The resulting arrangement may be used for touch or optical user interfaces and other purposes.

Abstract: Techniques for comparing 3D models are provided. A method for comparing 3D models includes obtaining a first skeleton of a first 3D model, obtaining a second skeleton of a second 3D model, and calculating similarity between the first and the second 3D models based on distance, angle, and inter-position related global constraints of the first and the second skeletons.

Abstract: Provided are devices, methods and recording mediums for processing video data including setting at least one particle on a target in an image of a previously-selected frame in a video, sequentially acquiring temporally-previous frames and temporally-next frames in the video after the previously-selected frame, determining a part whose difference in pixel values between the image of the acquired previous frame and the image of the next frame is a threshold or more and which corresponds to the target in the image of the previous frame as an outer edge of a particle tracking range, and setting the particles in the image of the next frame at positions of pixels which are within the outer edge of the tracking range, and specifying a position of the target in the image of the next frame based on the positions of the set particles.

Abstract: Data segmenting apparatus and method are provided. An apparatus for segmenting an input data sequence includes: a boundary searching device configured to search for one or more candidate boundaries in the data sequence, to obtain one or more candidate segmenting schemes formed by different combinations of these candidate boundaries; and an evaluating device configured to generate, for each candidate segmenting scheme, an evaluation value of each candidate boundary in the scheme by evaluating a segmenting loss caused by using the candidate boundary to segment the data sequence, and determine whether the candidate boundary is valid in the candidate segmenting scheme according to the evaluation value reflecting association relationship between a pair of adjacent data segments adjoining to the candidate boundary and association relationship between each of one or more pairs of non-adjacent data segments, each of which includes two non-adjacent data segments located at two sides of the candidate boundary.

Abstract: Systems and methods for matching a received image with a template image are disclosed herein. Such systems and methods can advantageously enable an image captured by a mobile device (such as a smartphone or digital camera) to be correctly identified by the processing application. In some embodiments, the received image is first resized in one or both dimensions in order to match or approximately match the dimensions of a given template. The received image and template image can then be superimposed. Next, an optimal translative transformation value can be calculated in order to generate a confidence level for the current possible match. After confidence levels for each template are generated and recorded, the template with the highest confidence level can be selected as the best match for the received image.

Abstract: Systems and methods for measuring consistency between two objects based upon a rank of object elements instead of based upon the values of those object elements. Objects being compared can be represented by d-dimension feature vectors, U and V, where each dimension includes an associated value. U and V can be converted to rank vectors, P and Q, where values of U and V dimensions are replaced by an ordered rank or a function thereof. Analysis directed to the consistency between U and V can be accomplished by determining consistency between P and Q, which can be more efficient and more accurate, particularly with regard to illumination-invariant comparisons.

Abstract: Provided are image processing method and apparatus. The method includes selecting one of a plurality of images matched in structure as reference image, and select another of the images as subject image; for a subject pixel in the subject image, determining a pixel corresponding to the subject pixel in the reference image; calculating similarity values of at least part of pixels in the reference image with respect to the pixel corresponding to the subject pixel; establishing weight coefficients based on the similarity values, and weighted averaging the subject pixel in the subject image to obtain a processed pixel value. With the above solutions, it is possible to use structure information of a higher-quality image in processing another image, and thus improve quality of the other image.

Abstract: The present invention is a system comprising image capture device, such as a scanner or digital camera connected to a computer processor that is able to capture and store images, and method of using the same for storing and processing expense receipts. The computer processor analyzes the images of the receipts, converts the images to text, analyzes the data, extracts expense data, and puts the data into an expense report. The end user can review the captured expense data, correct it or add to it. Preferably, the system displays the image of the receipt side-by-side with the captured expense data to make review and editing easier. In a preferred embodiment the image capture device is portable, such as a handheld scanner or digital camera, so that a user can scan receipts while traveling and discard the receipt. Also, in a preferred embodiment, the images are encrypted to prevent tampering by the user or a third party, and thereby preserve the integrity of the receipt image.