In the computer memory generally all the documents are stored in the form of gray level which has a maximum 256 different gray values from 0 to 255. Each gray value generates the different color of the gray scale palette. If some information is required from the document image, then this is required to process the action number of times. To reduce this time requirement for extracting the part of the image, binary image is more useful.
Binarization is the method of converting any gray – scale image (multi tone image) into black – white image (two tone image) . To perform binarization process, first find the threshold value of gray scale and check whether a pixel having a particular gray value or not.
If the gray value of the pixels is greater than the threshold, then those pixels are converted into the white . Similarly if the gray value of the pixels is lesser than the threshold, then those pixels are converted into the black .
There is two type of binarization method is discuss below –
i. Binarization based on Global or Single Threshold
ii. Binarization based on Region
1. Binarization based on Global or Single Threshold: Normally, find the global threshold for the whole image and binarize the image using single threshold. But in this single threshold method generally the local variance of the image is lost or suppressed which may be having some important information or contents.
2. Binarization based on Region: One another method is also designed for binarization in which threshold decide according to the region. Actually the image is divided into several regions or windows. Each region or window calculate or decide their own local threshold and then convert their region into two – tone region by the help of their local threshold according of the Saha .
The binarization process is failed in the practical scenario because of degradation may be occur due to less efficient acquisition process of image, poor quality of original source or non – uniform illumination over the original source.
Fig. 1 shows the original image in gray scale mode with multi tone and Fig. 2. shows their resultant binarized image in two tone.
- Satadal Saha, Subhadip Basu and Mita Nasipuri, “Automatic Localization and Recognition of License Plate Characters for Indian Vehicles,” in International Journal of Computer Science and Emerging Technologies, (IJCSET), UK, ISSN: 2044-6004, vol. 2, no. 4, pp. 520-533, Aug. 2011.