The present invention relates to binarization programs, and is particularly directed to a method of selecting a binarization program based upon image data which has been obtained from scanning a document such as a bank check.
In known check processing applications in which gray scale image data is obtained from scanning a bank check, two or more binarization programs may be applied to the same gray scale image data to extract a corresponding number of binary images of the check. The extracted binary images are then compared to identify the binary image of the best image quality. A disadvantage in applying two or more binarization programs to gray scale image data to extract a corresponding number of binary images of the check is that computational costs are relatively high.
In accordance with one aspect of the present invention, a document processing apparatus comprises a scanner for scanning a bank check to obtain gray scale image data associated with the bank check. A processor is provided for (i) selecting one of a plurality of binarization programs based upon the gray scale image data, and (ii) applying the binarization program selected to at least a portion of the gray scale image data to provide a binary image of at least a portion of the bank check.
Preferably, the processor includes a neural network which is applied to at least one value which has been calculated based upon the gray scale image data. The neural network may accept as input a value indicative of average intensity of pixels associated with the check. The neural network may also accept as input a value indicative of standard deviation of pixels associated with the check. The neural network may also accept as input a value indicative of histogram type of pixels associated with the check.
In accordance with another aspect of the present invention, a method of processing a bank check comprises the steps of (a) scanning the bank check to obtain gray scale image data associated with the bank check, (b) selecting one of a plurality of binarization programs based upon the gray scale image data obtained in step (a), and (c) applying the binarization program selected in step (b) to at least a portion of the gray scale image data obtained in step (a) to provide a binary image of at least a portion of the bank check.
Preferably, step (b) includes the step of (b-1) applying a neural network to at least one value which has been calculated based upon the gray scale image data obtained in step (a). Step (b-1) may include the step of accepting as input a value indicative of an average intensity of pixels associated with the check, accepting as input a value indicative of standard deviation of intensity of pixels associated with the check, or accepting as input a value indicative of histogram type of pixels associated with the check.