Enhanced Techniques for PDF Image Segmentation and Text Extraction
This work addresses the difficulty of automatic text extraction from PDF images for tasks like annotation and indexing, but it appears incremental as it builds on existing methods.
The paper tackled the challenging problem of extracting text from PDF images by enhancing two block-based classification techniques, reporting performance metrics for segmentation and time consumption.
Extracting text objects from the PDF images is a challenging problem. The text data present in the PDF images contain certain useful information for automatic annotation, indexing etc. However variations of the text due to differences in text style, font, size, orientation, alignment as well as complex structure make the problem of automatic text extraction extremely difficult and challenging job. This paper presents two techniques under block-based classification. After a brief introduction of the classification methods, two methods were enhanced and results were evaluated. The performance metrics for segmentation and time consumption are tested for both the models.