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

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, configured to:
• receive an image that depicts handwritten text;
• determine that a section of the image includes the handwritten text;
• analyze, using a first image processing technique, the section to identify subsections of the section that include individual words of the handwritten text;
• reconfigure, using a second image processing technique, the subsections to create preprocessed word images of the individual words;
• convert, using a word recognition model, the preprocessed word images to digital text that is associated with the preprocessed word images;
• and
• store the digital text in a data structure of a data management system.

A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a device, cause the device to:
• receive an image that depicts handwritten text;
• determine that a section of the image includes a portion of the handwritten text;
• analyze the section to identify a subsection of the section that is associated with individual word of the portion of the handwritten text;
• reconfigure the subsection to create a preprocessed word image of the individual word;
• convert, using a machine learning model, the preprocessed word image to a digital word that is associated with the preprocessed word image;
• determine, based on a sequence of subsections of the section, a sequence identifier of the digital word;
• generate, based on the sequence identifier and the digital word, digital text associated with the image;
• and
• perform an action associated with the digital text.