Scalable structure learning via context-free recursive document decomposition
AssigneeInternational Business Machines Corporation
InventorsMunish Goyal, Avinash Arya
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Abstract
An approach is provided in which the approach aggregates a set of pixel values from a bitmap image into a set of row sum values and a set of column sum values. The bitmap image is a pixelated representation of a document. The approach applies a localized Fourier transform to the set of row sum values and the set of column sum values to generate frequency representations of the set of row sum values and the set of frequency sum values. The approach decomposes the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations, and sends the set of image portions to a text recognition system.
Claims20
A method comprising:
- aggregating a set of pixel values from a bitmap image into a set of row sum values and a set of column sum values, wherein the bitmap image is a pixelated representation of a document;
- applying a localized Fourier transform to the set of row sum values and the set of column sum values to generate a set of frequency representations of the set of row sum values and the set of column sum values;
- decomposing the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations;
- and
- sending the set of image portions to a text recognition system.
The method of 1 wherein the set of image portions comprise a first image portion and a second image portion, the method further comprising:
- aggregating a subset of pixel values from the first image portion into a subset of row sum values and a subset of column sum values;
- applying the localized Fourier transform to the subset of row sum values and the subset of column sum values to generate a subset of frequency representations;
- and
- recursively decomposing the first image portion into a third image portion and a fourth image portion based on at least one different separation location identified in the subset of frequency representations.
An information handling system comprising:
- one or more processors;
- a memory coupled to at least one of the processors;
- a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of:
- aggregating a set of pixel values from a bitmap image into a set of row sum values and a set of column sum values, wherein the bitmap image is a pixelated representation of a document;
- applying a localized Fourier transform to the set of row sum values and the set of column sum values to generate a set of frequency representations of the set of row sum values and the set of column sum values;
- decomposing the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations;
- and
- sending the set of image portions to a text recognition system.
A computer program product stored in a computer readable storage medium, comprising computer program code that, when executed by an information handling system, causes the information handling system to perform actions comprising:
- aggregating a set of pixel values from a bitmap image into a set of row sum values and a set of column sum values, wherein the bitmap image is a pixelated representation of a document;
- applying a localized Fourier transform to the set of row sum values and the set of column sum values to generate a set of frequency representations of the set of row sum values and the set of column sum values;
- decomposing the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations;
- and
- sending the set of image portions to a text recognition system.
Dependencies are inferred from the claim text.