An improved binarization algorithm based on a water flow model for document image with inhomogeneous backgrounds

Designing the Yellow Head Virus Syndrome Recognition Application for Shrimp on an Embedded System

“…In the local adaptive technique, a threshold is calculated for each pixel, based on some local statistics such as range, variance, or surface-fitting parameters of the neighboring pixels. It can be approached in different ways, such as background subtraction (Lu et al, 2010), water flow model (Oh et al, 2005), mean and standard derivation of pixel values (Sauvola and Pietikäinen, 2000) and local image contrast (Su et al, 2010). Some drawbacks of the local thresholding techniques are region size dependant, individual image characteristics, and time-consuming.…”

Enhanced Text Extraction from Arabic Degraded Document Images Using EM Algorithm

“…These evaluations include comparative results between the proposed method and some known binarization algorithms [8,11,12,13,14]. Moreover an average performance score is computed for global decision.…”

“…Gatos et al [8] presents a binarization methodology based on background estimation used to segment the image, various pre-and post-processing steps are needs in this approach. Oh et al [12] presents an iterative algorithm based on water flow models and a hierarchical thresholding. This method deals with low contrasted documents images.…”

Analysis of multi-homed SCTP and delay-centric transmission for VoIP traffic in lossy networks

“…Several papers in the literature addressed the back-to-front interference problem. Some authors use waterflow models [3], other researchers have used wavelet filtering [4], but the technique of most widespread use is thresholding [5]- [6]- [7]. The most successful techniques for filtering out back-tofront interference are based on the entropy [8] of the greyscale document [9]- [10].…”