System and methods for multiple imaging element scanning and copying

A scanning or copying system can include imaging elements and one or more system processors that are programmed or adapted to perform image processing methods and algorithms on image data, and in some instances, to enhance the image. Image data is acquired using imaging elements. Some imaging elements may have overlapping or rotated fields of view or employ differing resolutions. For each imaging element, its output is recombined together with the output of one or more other imaging elements. To perform the recombination, the system can extract features in an overlapping region and match these features in multiple images. In some instances, the features matched can be edges. Alternatively, the recombination can be performed by positioning each subimage with respect to a larger image through image matching and location techniques. Parameters from the recombined image can be extracted and these parameters can be used to correct for geometrical and spatial distortions and thereby enhance the image.

BACKGROUND

The present invention is directed to systems and methods for scanning documents. More specifically, without limitation, in one embodiment, the present invention relates to systems and methods that employ a plurality of imaging elements that can capture an upward facing document under normal illumination, process plural images, correct for geometrical and other forms of distortions, and reconstruct the image for scanning, displaying, copying, distributing, and storage.

Traditional scanning or copying systems require the document to be placed upside down on a transparent platform. Under the platform, a special illumination system illuminates lines or portions of the document sequentially while imagers or light sensors capture the reflected light to form an undistorted and balanced image of the document. The use of motion components to facilitate the scanning process often hinders performance and adds to both the initial cost and maintenance cost of the system. The traditional design renders use of scanning and copying equipment counterintuitive and inconvenient to use. For example, when a user needs to copy from a thick bound volume of a journal, the user may need to turn the volume upside down and apply sufficient forces with both hands so that the central margins of the pages lie as flat as possible and are therefore not severely distorted and defocused. This process may also create stress and damage to the volume.

These and other disadvantages of known techniques are solved in one embodiment of the present invention by the use of an opto-mechanical imaging system employing multiple imaging elements in conjunction with image processing algorithms. For example, when a user reads a document such as a book, the imaging element array can capture the images of opened pages of the book and processes the images to reconstruct the image to ideal format and clarity. The user need only turn the pages and command the scanning or copying with the disclosed system. The disclosed system may be combined with a system for displaying or printing.

The rapid development of image sensors built using newer technologies such as CCD and CMOS technologies has led to digital sensors that are orders of magnitude more sensitive. Additionally, these sensors are relatively inexpensive, particularly when manufactured in high volume. High-performance hardware to facilitate post-processing has also become inexpensive.

Systems that employ a “camera-like” setup to capture a document such as a bound book for scanning and copying have been the subject of at least one U.S. Patent (U.S. Pat. No. 5,969,795 to Honda). However, one embodiment of the present invention discloses an innovative scheme that employs a plurality of imagers, image processing algorithms, and processing hardware in such a way that a high-quality, high-performance, yet inexpensive, easy to use device can be made to scan or copy a document face-up.

SUMMARY

In one embodiment, the present invention is directed to systems and methods of using an array of imaging elements to scan an upward facing document under normal illumination. The image generation system includes three components: an opto-mechanical system, an image processing hardware configuration, and image processing algorithms and methods.

In some embodiments, the present invention uses an array of imaging elements with overlapping view fields, although other embodiments need not be limited to an array configuration of image elements. The opto-mechanical system includes an imaging system. The imaging system includes the imaging elements that image the document. In one embodiment, the imaging system includes an array of imaging elements, such as CCD or CMOS imagers and corresponding focusing optics. In some embodiments, the opto-mechanical system can also include an illumination system to provide adequate uniform illumination of the document to be imaged. This illumination system can, in some embodiments, be integrated with the imaging system as an arrangement (such as an array) of illumination elements that is housed with the imaging elements. In one embodiment, the imaging elements and illumination elements are arranged in a manner allowing easy rearrangement by the user to generate the best quality and/or resolution for a document of a given size.

One embodiment of the present invention is particularly useful for the scanning of open books or other objects that do not naturally lie flat. To better image such surfaces, in some embodiments, the imaging elements can also be angled such that the areas imaged by adjacent imaging elements are not overlapping. This angling of the imaging elements serves the function of allowing the imaging of angled surfaces without, or with reduced, distortion and defocus. In some embodiments, the angling of individual and/or groups of imaging elements, and/or illumination elements when present, can be controlled by the user in an arrangement to improve imaging quality.

In some embodiments, the imaging elements can be configured at different resolutions with differing viewing areas. For example, an imaging element can have an area of view covering the entire scan surface at a first resolution. Additional imaging elements can be positioned central to each of several quadrants that comprise the entire scan surface having an area of view covering each respective quadrant at a second resolution. Additional subdivision of quadrants can occur with other imaging elements covering the subdivisions. Alternate embodiments can use differing number of quadrants and imaging elements. The resolution of each imaging element can be selectively controlled to set resolution and areas of view based upon scanning requirements.

The present invention can include image-processing hardware that receives data from the imaging elements. In different embodiments, the image-processing hardware can include a range of parallelization. In one embodiment, a single processing element receives data in a serial fashion from the imaging elements. This data from individual imaging elements is recombined and further processed to generate the final image. In a second embodiment, a processing element such as a digital signal processing (DSP) element, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a programmed general purpose processor is allocated for a grouping of imaging elements; for example, in an array configuration one processing element can be allocated per row, column, row portion, column portion or subarray of predetermined row and column size. In such an embodiment, group-wise stitching, recombination, and processing can occur in each of these elements with processed groups and extracted features, parameters and/or other appropriate statistics being passed to another processing element for further processing of the groups. Finally, in a third embodiment, each imaging element incorporates a processing element that performs localized processing of locally derived data and can perform integration of locally processed data from neighboring imaging elements. Global processing of the image, if needed, can occur via a central processing element. In all embodiments, imaging elements can be calibrated at the pixel level.

Finally, software based processing of the images can occur. The software process can recombine or stitch the partial images generated from each imaging element through a registration process. Feature extraction can occur for each partial image, and the partial images can be stitched together through identifying the same feature in adjacent partial images. In one embodiment, edges form the feature set used for the registration and stitching processes. The registration algorithm for recombining together co-planar partial images can account for potential illumination and curvature artifacts. In some embodiments, the present invention can join images by identifying joints by comparing partial images with a lower resolution image that includes the overlap region between the partial images. Alternatively, the present invention can use the approach disclosed in expired U.S. Pat. No. 4,393,410 to Ridge et al., the content of which is incorporated herein by this reference.

The fully recombined image can be further processed to extract parameters for correcting geometrical, spatial and lighting artifacts, and these parameters can then be used for image correction. Further image enhancement to improve output quality can also occur.

DETAILED DESCRIPTION

As used herein, the following terms shall be defined in accordance with the definitions provided:Imaging element: a component that forms an image of a physical area. It may comprise an optical portion and a sensor (imager) portion. A digital camera is an example of an imaging element.Area of View: the physical area that is imaged by the optics of an imaging element onto the imager and recorded by the imager. It is equivalent to field of view.Resolution: the capability of an imaging system to record or render image details, represented by the number of pixels in the image space representing unit distance in the object space. Assuming sufficient optical resolution with the corresponding optical components, resolution is determined by the number of photosites in the photo sensor array or imager.Subset: any combination of any number of elements from a larger set, including but no limited to the null and empty sets.
Opto-Mechanical System

In some embodiments, the opto-mechanical system includes two major subsystems as shown inFIG. 1. These subsystems might include an imaging subsystem that includes a set of imaging elements105, such as that depicted in an array configuration, and an illumination subsystem, such as with depicted integrated light sources110, such as light emitting diodes (LEDs). The imaging elements can be arranged in any suitable configuration appropriate for the imaging task to be performed; in some exemplary embodiments, the imaging elements are arranged in a two-dimensional configuration. Many such embodiments configure the imaging elements in a two dimensional array; although other embodiments could include a concentric circle or other suitable arrangement. In other embodiments, the imaging elements need not be confined to two dimensions but could be arranged in a suitable three-dimensional configuration. Other embodiments need not include an illumination subsystem, or may optionally provide illumination through a separately provided system. The configuration of imaging elements can consist of a sufficient number of imaging elements so that the resolution of the acquired images is adequate for the intended application purpose. If the desired scan or copy resolution is R pixels/inch (assuming uniform resolution for both horizontal and vertical dimension), the number of useful pixels of the imaging element is P (assuming square pixel), and the size of the to be scanned document115is S1×S2inches, then the minimum number of imaging elements needed can be given by (S1×S2×R2)/P. This formulation for the minimum number of imaging elements is intended as a non-limiting example and other formulations are possible.

Any suitable type, or combination of types, of image forming devices can serve as imaging elements. In some exemplary embodiments, CCD imagers, CMOS imagers and/or combinations thereof can serve as the imaging elements. The optical lenses for any imager can be a telephoto lens such that it covers a portion of the document with minimum distortion or other optical aberrations. Other types of lenses can be used as appropriate. To provide adequate uniform illumination for the imaging elements array, the illumination system can be housed with the imaging elements. Alternatively, it can be housed externally. Some exemplary embodiments do not include an illumination system or subsystem.

In some embodiments, the illumination system can consist of an arrangement of LEDs. In one embodiment, the illumination system can be arranged in one or more arrays. Selection of the LEDs can be based on the sensitivity of the imagers. As a non-limiting example, for monochromatic scanning and copying, infrared LEDs and infrared sensitive imagers can be used. Such an array, or arrays, of LEDs or other types of efficient light sources can form an illumination subsystem.

In other embodiments, the illumination system can use one or more fluorescent lamps to provide normal illumination for the user and/or the imaging elements. Selection of fluorescent lamps can be based on their spectral compositions. As a non-limiting example, to achieve greater efficiency, the spectral energy distribution curves of the fluorescent lamps can be chosen to overlap with the spectral sensitivity curves of the imagers.

The imager and illumination systems can be constructed or arranged so that they can be conveniently arranged by the user so that a desired resolution can be achieved. The arrangement can be based on the dimensions of the document to be scanned or copied or the orientation and/or known/detected irregularities of the document. For typical applications such as scanning and copying of bound books115, the configuration ofFIG. 1can be used. In some embodiments, the imaging elements can be arranged such that they are not more than two elements deep in a given dimension. Thus, the matrix could be a 2×N or an N×2 matrix where N is an integer greater than or equal to one. Those skilled in the art will realize that other configurations of imaging elements are possible.

In some embodiments, the imaging elements can be configured at different resolutions with differing areas of viewing. For example, a central imaging element can have an area of view covering the entire scan surface at a first resolution. Four additional imaging elements can be positioned central to each of four equally sized quadrants that comprise the entire scan surface having an area of view covering each respective quadrant at a second resolution. Additional subdivision of quadrants can occur with centralized imaging elements covering the subdivisions. Alternate embodiments can use differing numbers of quadrants and imaging elements. Additionally, other geometric formulations are possible such as concentric circles of imaging elements. The resolution of each imaging element can be selectively controlled to set resolution and areas of view based upon scanning requirements.

In some embodiments, the imaging elements can be configured in such a manner so that some imaging elements can be designated for a specific task. As a non-limiting example,FIG. 10shows one such embodiment. The configuration ofFIG. 10shows the Area of View (AOV) divided into four sub areas. The “LEVEL 0” division1005creates a center of the whole AOV for imaging element c0and four sub AOV imaging elements imaged by imaging elements at positions c1. The “LEVEL 1”1010division further divides each of the four sub AOVs into four additional sub AOVs, creating four new positions for four c1imaging elements. Similarly, further dividing at “LEVEL 2”1015creates center positions for 16 imaging elements c2and 64 sub AOVs. Following this approach, any resolution can be obtained by further dividing the sub AOVs according to application requirements.

Imaging elements c0, c1, c2, etc. can be of the same or different sensor resolutions. Additionally, different types of optical elements can be included in the imaging elements to generate different, potentially controllably different, areas of view. As a result of differences in the area of view, the captured images can have different resolutions. Images at lower resolutions can provide data for global document surface structure and luminance corrections, image stitching verification, and other image processing as appropriate. This processing can be accomplished at a faster rate due to the design of the system. The system architecture can also provide fast preview images or final scanned images at lower resolutions.

Images at multiple resolutions acquired individually can provide useful information for improved and accelerated data processing to assemble any final high resolution image.

When scanning or copying a bound volume such as a book, the exposed pages are usually not flat. The shapes of the two exposed pages of an opened book usually depend on the thickness of the book and the binding method used. When a book is scanned or copied with a conventional face-down scanner, such binding structure can create a distorted and defocused section in the reproduced pages. To overcome this and other limitations, one embodiment of the present invention can arrange the middle two or more columns of imaging elements to orient in a manner that reduces such distortion and defocus. In one exemplary embodiment, the middle two columns of imaging elements can be oriented at opposite angles.FIG. 8shows two imaging elements805,810oriented such that they have overlapping areas of view. In another exemplary embodiment shown inFIG. 9, the imaging elements are arranged in an array of the dimensions of 4×4. As a result of this orientation, column2905and column3910have swapped areas of view. As shown inFIG. 9, the dotted borders around each imaging element represent the area of view of its corresponding imaging element in the other column. Such orientation arrangement can be conveniently practiced with a manual or automated orientation adjustment system. Mechanisms that automatically detect the location of the spine of a book that is being imaged can be used. Such mechanisms can use well-known image processing techniques for object detection and location such as described below. This positional information can be used to control the angling of different imaging elements.

Image Processing Hardware Implementation

There exist numerous strategies in hardware and software for further processing of output from the imagers in the above described opto-mechanical system. These strategies are dependent on the degree of image processing parallelization.

In at least one embodiment, the image enhancement system includes a system processor including one or more processing elements. The term processing element (PE) may refer to (1) a process running on a particular piece, or across particular pieces, of hardware, (2) a particular piece of hardware, or either (1) or (2) as the context allows. Each processing element may be supported via a standard general purpose processor such as an Intel-compatible processor platform preferably using at least one PENTIUM or CELERON (Intel Corp., Santa Clara, Calif.) class processor; alternative processors such as UltraSPARC (Sun Microsystems, Palo Alto, Calif.) could be used in other embodiments. ARM and/or MIPS RISC processors could also be used in some embodiments.

In addition, or instead, one or more special purpose processors such as digital signal processing (DSP) elements can be included. A DSP element may be one or more of a Texas Instruments DSP such as TMS320C6411, TMS320VC5501 or Analog Devices DSP such as ADSP-21532S. DSP elements, and processors with similar capabilities, are processing elements (PEs) for the purposes of this specification.

FIG. 6is a block diagram depicting elements in one exemplary embodiment performing several image processing steps. The depicted image-processing pipeline can implement various feature and parameter extraction, image correction and enhancement methods. Depending on the embodiment, one or more processing blocks may be implemented with one or more processing elements depending on the performance of the processing elements and hardware architecture.

The system processor, or the processing elements thereof, may also include one or more application specific integrated circuits (ASICs) and/or field programmable gate arrays (FPGAs). ASICS or specially programmed FPGAs can perform various functions required of the system processor. In some embodiments, the system, or the processing elements thereof, may include a combination of general purpose processors, ASICs, DSPs and/or FPGAs. In some embodiments, image enhancement functionality, as further described below, may be distributed across multiple processing elements.

Furthermore, one skilled in the art will recognize that when reference is made to performing operations first on columns then on rows, the order of operations can be reversed such that rows are processed before columns with minimal modification. In addition, such embodiments need not be limited to row or column arrangements. Other grouping arrangements for processing and analysis are contemplated within the scope of the present invention.

Central Processor System

In some embodiments, one central processing element210manages all M×N possible imaging elements205via a suitable interface215. After image acquisition by the individual imagers205, the images can be recombined together in a serial fashion. Feature extraction can then be performed. Central processing element210can use memory220for the combination process as well as other image manipulations. One such exemplary system is depicted inFIG. 2. In some embodiments, after feature and parameter extraction have been performed, spatial unwarping can then be performed and nonuniform lighting effects can be corrected. The output of this state can be further processed for background removal, text/image segmentation and enhancement before final output. Additional image processing can be performed as appropriate. Such an approach is described in greater detail in commonly assigned U.S. patent application Ser. No. 10/224,660, filed Aug. 20, 2002, entitled “Systems and Methods for Content-Based Document Enhancement”; the content of which is hereby incorporated by this reference herein for all purposes.

Balanced System

In other exemplary embodiments, some parallelism can be exploited based on imaging elements rows. As a non-limiting example, a 4×3 camera acquisition matrix305can be formed with individual processor elements335dedicated for each imaging element matrix row. One such exemplary system is depicted inFIG. 3. Each processing element310can include one or more DSPs, ASICs, FPGAs, general purpose processors or other processing units. Memory storage315can also be incorporated locally, and/or as a shared memory space. Each processing element335can perform the various tasks including, but not limited to, group-wise recombination, distortion correction, and illumination compensation. As shown inFIG. 3, a PE can be partitioned to process different rows of imaging elements310. PEs can efficiently recombine the images from the output data from each band of data from the imaging elements. Thus, the amount of local and band image/data processing that can be performed is dependent on the performance of each PE. This sets the granularity of the image processing operations. The column-wise processing element320can perform recombination of the bands in the vertical direction of corrected data from the row wise PEs330. In addition to image data, statistics can be passed on to the next processing stage. The next stage of processing can apply further corrections and enhancements as necessary across the bands. Additional stages of processing can occur depending upon the granularity and performance of the PEs and imaging elements. The row and column processing described above was selected as exemplary; other embodiments can selectively process in other, sometimes user configurable, groupings of imaging elements.

Full Parallel System

In some other exemplary embodiments, each imaging element can have its own processing element, or elements. These processing elements can be of lower performance than those of the two previous sets of exemplary embodiments. Such embodiments readily support image recombination because each imaging element output can be passed through any neighbor. An exemplary system is depicted inFIG. 4. As a non-limiting example, the processing element on the top left405can initiate a block transfer to its neighbor on its right410and the data can thereby propagate through its neighbor410. The block transfers are not limited to left and right neighbors but can also transfer to its neighbor above and below. As one skilled in the art will recognize, other directions of data transfer, including diagonal, can be implemented. The neighbor can then correlate the incoming data for overlapping regions and recombine the incoming image with its own internal image. This process can be repeated as many times as necessary as data is transported from left to right. The farthest right neighbor415performs the same functions before it transports the data to a global area processing element or elements420. The global area processing element420can then apply additional corrections and enhancements to the whole image. In some embodiments, localized statistical information can be generated and/or distributed. This allows for better image processing and correction of the data. If processing element communication between upper and lower rows of elements is not implemented, then the global area processing element can be used to recombine together the multiple horizontal image strips.

In some embodiments, a hierarchical processing organization can be used. For example, in some embodiments using lower resolution central imaging elements, locally processed subimages can be passed to the processing element of the lower resolution central imager for joining and potential propagation to a further lower resolution central imaging element. Document recombination, or stitching, can be achieved by resampling the subimage to reduce its resolution to that of the lower resolution image and then finding its position on the lower resolution image by repeatedly shifting and computing the correlation of the subimage with the lower resolution image. Alternatively, the image joining process described in considered U.S. Pat. No. 4,393,410, issued to Ridge et al. can be employed. The content of this disclosure is hereby incorporated herein by this reference.

Image Processing Methods and Algorithms

According to one embodiment, the image processing methods and algorithms of the present invention have the ultimate purpose of collecting and recombining together the images produced by each imaging element. One skilled in the art will realize the methods and algorithms described below can be applied to any of the three processing schemes described above. In an exemplary embodiment, registration of a pair of images commences by extraction of some features in the overlapping region and the matching of these features in both images. An exemplary process is shown inFIG. 5. In one embodiment, edges are used as the relevant feature set. Since the positions of the imaging elements can be determined, the search area505can be of a small size. Edges provide important information about details in the image. Once edges in the overlapping regions have been extracted, images can be stitched together by matching edges from one image to its neighboring images. This can be done using template matching or correlation techniques.

In one embodiment, template matching can be used to perform pattern classification. In this process, the edges of one image, or template, are moved to possible positions in a second image. The number of matches (edge pixels in the template that are matching those in the second image) can be counted. The maximum correlation approach picks the position that has the maximum number of matches. The minimum error approach counts the number of mismatches and picks the position with the minimum number of mismatches. As one skilled in the art will recognize, other methods of image matching may be used.

An exemplary image processing system overview and architecture are shown inFIGS. 6 and 7, respectively. Once the registration process is complete, the image can then be processed to correct for any geometrical and spatial distortions in addition to illumination adjustment and output quality improvement. This processing can be accomplished by extraction of A and B feature sets.

“A” Parameter Set

The A set are parameters extracted from the recombined image to determine the orientation and correct for distortions. One skilled in the art will recognize the following three steps as exemplary and that individual steps may be removed or combined with other steps.

The image can be blurred using a 3×3 kernel to remove noise and suppress moire. This step can be useful in the subsequent binarization of the image. In one embodiment, the kernel can be of the following form:

The image can be thresholded710using dynamic thresholds to extract the text and images. In one exemplary embodiment, a local adaptive threshold is used. It has been found that a local adaptive threshold can be more effective in separating text/images from background since images captured with an imaging element generally have fluctuating luminance and therefore cannot be binarized optimally. III. Line curve detection

Once the image is binarized, a line detection algorithm can be applied715to determine the orientation and distortion of the page. In one exemplary embodiment, this can be done by convolving the image with a set of nine masks that represent bases for edge, line, and average subspaces. Other methods of determining the orientation and distortion can be used as appropriate. The resulting responses at a pixel are treated as components of a vector. Projecting this vector onto the edge and line subspaces indicates the relative “edgeness” of “lineness” at a point. The slope and direction of these lines constitute the A parameter set720.

“B” Parameter Set

Following processing for the A parameter set, the B parameter set725can be processed. This step can include the extraction of a feature vector that describes the gray level distribution of the image730. The components of the feature vector can include gray values, filtered gray values, texture measures, Markov random field features, fractal dimension measures, gradient magnitudes and directions, and/or other known components. In one exemplary embodiment, the feature vector can be constructed from statistical measurements obtained from image histogram and directional edge information. This feature set can be useful in segmenting the page into text, graphics and background. Each component can be enhanced appropriately.

Image Correction

Using the A set parameters, an image can be warped to correct for geometrical and spatial distortions735. Image warping is the act of distorting a source image into a destination image according to a mapping function between source space (u, v) and destination space (x, y). The mapping can be specified by the functions x(u, v) and y(u, v). Different types of mapping can be implemented in the instant invention, such as piecewise, bilinear, biquadratic, and/or bicubic. Other types of mapping can be used as appropriate. Such mappings can be parameterized by a grid of control points.

Image warping can also be done in a multi-resolution scheme. One advantage of this approach is that features that might be undetected at one resolution may be readily detected at another resolution. Additionally, since fewer details are present at low resolution, the matching process can be computationally less expensive. In one embodiment, at least one low resolution image can be acquired representing a large portion of a document. This image can function as a guidance map. The details of the document can be captured using a set of overlapping high-resolution images. The lower resolution image can be used as a map to guide the stitching process. This can be accomplished by converting the high resolution images into lower resolution images using subsampling or a more involved process such as wavelet transforms. The A set can be extracted from the resulting images and can be compared with an image obtained from the low-resolution map. This registration step can provide an initial estimate of the position of the images with respect to the whole document. In some embodiments, fine adjustments can be performed at higher resolutions.

The B set can be used to enhance the output image740. These enhancements can include, but are not limited to, background suppression, noise removal, and sharpening of text. Eliminating substantially all background gray values can improve the quality of the scanned image. In some embodiments, different filters can be applied to different document components as follows:a) If the pixel is classified as text in the B set, the following sharpening kernel Ksh, can be applied:

Ksh=[-1-1-1-19-1-1-1-1](2)b) If the pixel is classified as image in the B set, the following smoothing kernel, Ksm, can be applied:

One skilled in the art will recognize that other filters and/or kernels can be used as appropriate.

Throughout this application, various publications may have been referenced. The disclosures of these publications in their entireties are hereby incorporated by reference into this application in order to more fully describe the state of the art to which this invention pertains.

The embodiments described above are given as illustrative examples only. It will be readily appreciated by those skilled in the art that many deviations may be made from the specific embodiments disclosed in this specification without departing from the invention. Accordingly, the scope of the invention is to be determined by the claims below rather than being limited to the specifically described embodiments above.