A New Threshold Selection Method Based on Fuzzy Expert Systems for Separating Text from the Background of Document Images

• Published in: Iranian journal of science and technology. Transactions of electrical engineering 2019-07, Vol.43 (Suppl 1), p.219-231
• Main Authors: Annabestani, Mohsen, Saadatmand-Tarzjan, Mahdi
• Format: Article
• Language: English
• Subjects: Electrical Engineering; Engineering; Research Paper
• ISSN: 2228-6179; 2364-1827
• DOI: 10.1007/s40998-018-0160-7

Threshold selection for text segmentation is an essential preprocessing step in most document processing algorithms. Although there are a number of sophisticatedly well-trained methods for text extraction, many researchers still prefer a fast and simple threshold selection algorithm for preprocessing. In this paper, a new global threshold selection method is proposed based on fuzzy expert systems (FESs). It initially enhances image contrast by using a FES. Then, the range of the threshold value is adjusted by using another FES and a pixel-counting algorithm. Finally, the threshold value is obtained as the middle value of the above range. To evaluate the performance of the proposed algorithm, we employed a database of 20 English, Farsi, and Chinese document images. Experimental results demonstrated that our method provided superior solution quality compared to a number of well-known frequently used counterpart algorithms. The computational burden of the proposed algorithms is actually light with the computational complexity of O ( MN ) for the image of size M  ×  N .