Text line Segmentation in Compressed Representation of Handwritten Document using Tunneling Algorithm

Abstract

In this research work, we perform text line segmentation directly in compressed representation of an unconstraint handwritten document image using tunneling algorithm. In this relation, we make use of text line terminal point which is the current state-of-the-art that enables text line segmentation. The terminal points spotted along both margins (left and right) of a document image for every text line are considered as source and target respectively. The effort in spotting the terminal positions is performed directly in the compressed domain. The tunneling algorithm uses a single agent (or robot) to identify the coordinate positions in the compressed representation to perform text-line segmentation of the document. The agent starts at a source point and progressively tunnels a path routing in between two adjacent text lines and reaches the probable target. The agent's navigation path from source to the target bypassing obstacles, if any, results in segregating the two adjacent text lines. However, the target point would be known only when the agent reaches destination; this is applicable for all source points and henceforth we could analyze the correspondence between source and target nodes. In compressed representation of a document image, the continuous pixel values in a spatial domain are available in the form of batches known as whiteruns (background) and black-runs (foreground). These batches are considered as features of a document image represented in a Grid. Performing text-line segmentation using these features makes the system inexpensive when compared to spatial domain processing. Artificial Intelligence in Expert systems, dynamic programming and greedy strategies are employed for every search space while tunneling. An exhaustive experimentation is carried out on various benchmark datasets including ICDAR13 and the performances are reported.

FastSS: Fast and smooth segmentation of JPEG compressed printed text documents using DC and AC signal analysis

“…Analysis of text-line and word boundaries in printed text documents is a very significant problem in Document Image Analysis (DIA) [ 2 , 18 ]. It is a crucial preprocessing stage for many important applications like Word Spotting, Document Retrieval and OCR [ 18 , 25 ].…”

“…In the literature, compressed streams of various file formats have been analyzed, and different segmentation techniques are reported directly on the compressed streams [ 18 ]. Some of them are like Run length [ 2 , 18 ], JPEG [ 8 , 19 , 35 ], JBIG [ 28 , 39 ], JPEG2000 [ 6 , 15 ] and Fast H.264 [ 44 ]. Run length compressed domain approaches for text-line, Word and character segmentation are reported in [ 16 , 17 ].…”

“…This algorithm is applied directly on the run length compressed representation. Tunneling algorithm for tracing the text-line boundaries is proposed in [ 2 ]. Document segmentation using block activity is reported in JPEG compressed domain [ 8 ].…”