Document scanners are used to convert paper documents into electronic records. Documents scanners often include digital image processing in order to enhance images captured by the document scanner to improve the image quality and to extract information contained within the document. The improved image quality that results from the image processing allows more accurate downstream information extraction such as used in OCR processing, and clearer images when the processed digital images are printed. In many high volume document scanners, the image processing is implemented by embedding the image processing hardware and software into the scanner. For example, the Kodak model i5200 scanner includes embedded image processing to implement functions such as automatic color detection, autocrop, deskew, content-based blank page detection, multi-color dropout, and compression.
FIG. 2A represents an example of a prior art document scanner, connected to a PC, which includes embedded image processing hardware. In this example, document to be imaged 260 is captured by a camera 261 which converts the document into digital image data that is stored in buffer memory 262. The scanner performs pixel processing 263 to correct for any abnormal pixel information (i.e., correcting for illumination roll-off or dead CCD pixels, defect concealment and color correction) introduced by the scanner or camera before storing the pixel processed digital image data in image buffer 264. The image data stored in image buffer 264 is then analyzed and processed again by the image processing 265 before being sent to the network interface of the scanner 266. Typical image processing function performed by image processing 265 may include, for example, deskew, rotation, color-dropout, binarization and compression. Typically a PC 20 is attached to the scanner to capture the processed image output from the scanner 10 and to perform downstream processing as described above.
In some document scanners, in order to reduce cost, much of the image processing is performed by a generic PC attached to the scanner, rather than by hardware within the scanner. The PC then performs the image processing. For example, the Kodak model i1200 series scanner is an example of a low cost document scanner that requires a PC to perform the document image processing.
In some applications, there is a need for multiple scanners in the same facility. For example, a bank office typically has multiple bank tellers, and each bank teller can have a scanner at their work area. FIG. 2B shows an example of a prior art document scanning and processing system which could be used in such applications. The system includes three document scanners 10A, 10B, and 10C which connect to three personal computers 30A, 30B, and 30C over three different interfaces 20A, 20B, and 20C. The personal computers 30A, 30B, and 30C provide image processing for the corresponding scanner, and provide processed images over a network 40.
As requirements for faster scanning and more complex image processing is added to the scanner system, the performance and cost of the embedded hardware (and/or PC attached to the scanner) increases. As the costs of the scanner and PC increase, it becomes less attractive to the end user to purchase the scanner system as the cost payback period becomes longer. Even though a higher performance PC is required to support the full rated scanner throughput, many of these lower cost scanners are in venues having a lower daily throughput. Thus, they are not continuously scanning documents and the processing power in the higher performance PC goes un-utilized during these low scanning utilization periods.
In an alternate embodiment, a system described in commonly-assigned U.S. Pat. No. 7,353,998 B2, entitled “Image Processing System Receiving Simultaneous Scan requests From Multiple Scanners”, allows multiple scanners to be connected to a single central PC computer. This patent is incorporated by reference herein in its entirety. This prior art system suffers from being the bottleneck for the scanning process. In this system, the scanner has to first make a request to scan a document before it actually performs the scan. This creates latency where the scanner must wait for the resources to be allocated to the scanner. The scanner is a slave to the PC, which pulls the data instead of allowing the scanner to push the data at its rated speed. In addition, as the number of scanners and needed image processing increases, the cost of the central PC can increase dramatically.
In addition, some countries or markets (and businesses in general) cannot afford to purchase the latest high performance PC to attach to the scanner(s), thereby prohibiting the sale of costly scanner systems into these markets.
Thus, there remains a need to provide a low cost, high performance system providing scanner image processing in applications where multiple scanners are required.