Boosted Edge Detection Algorithm for Unstructured Environment in Document Using Optimized Text Region Detection

Abstract

Document images are more popular in today’s world and being made available over the internet for Information retrieval. The document images becomes a difficult task compared with digital texts and edge detection is an important task in the document image retrieval, edge detection indicates to the process of finding sharp discontinuation of characters in the document images. The single edge detection methods causing the weak gradient and edge missing problems adopts the method of combining global with local edge detection to extract edge. The global edge detection obtains the whole edges and uses to improve adaptive smooth filter algorithm based on canny operator. These combinations increase the detection efficiency and reduce the computational time. In addition, the proposed algorithm has been tested through real-time document retrieval system to detect the edges in unstructured environment and generate 2D maps. These maps contain the starting and destination points in addition to current positions of the objects. This proposed work enhancing the searching ability of the document to move towards the optimal solution and to verify the capability in terms of detection efficiency.