Accenture Global Solutions Limited

Debasmita Ghosh

Nidhi

Siddhanth Gupta

Snehlata Sinha

Saurav Mondal

Karna Rajesh Rewatkar

Dharmendra Shivnath Prasad Chaurasia

Asmita Mahajan

Nakul Aggarwal

Methods, systems, and apparatus are provided for detecting and extracting data from a nested table. A contour image of a first table disposed within a cell of a second table from an input image is identified. The first table on the input image is masked to generate a masked image of the second table that omits the first table. Cells of the first table and the second table are detected by identifying a plurality of regions of interest (ROIs), determining a row of a plurality of cells based on a common y-coordinate among of the plurality of ROIs, and generating cell parameter information for each of the plurality of cells that identifies the y-coordinate, a size, and a relative position of each determined cell. An output file is generated based on the cell parameter information of the plurality of cells.

Intelligent nested tables detection and text extraction from images and scanned documents

In some implementations, a device may receive an image that depicts handwritten text. The device may determine that a section of the image includes the handwritten text. The device may analyze, using a first image processing technique, the section to identify subsections of the section that include individual words of the handwritten text. The device may reconfigure, using a second image processing technique, the subsections to create preprocessed word images associated with the individual words. The device may analyze, using a word recognition model, the preprocessed word images to generate digitized words that are associated with the preprocessed word images. The device may verify, based on a reference data structure, that the digitized words correspond to recognized words of the word recognition model. The device may generate, based on verifying the digitized words, digital text according to a sequence of the digitized words in the section.

Utilizing machine learning and image filtering techniques to detect and analyze handwritten text

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Kolkata, India

Debasmita Ghosh