The data filtering based multiple-stage Levenberg–Marquardt algorithm for Hammerstein nonlinear systems

Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models

Summary This article researches the filtering‐based parameter estimation issues for a class of multivariate control systems with colored noise. A filtering‐based recursive generalized extended leas...

Filtering-based recursive least squares estimation approaches for multivariate equation-error systems by using the multiinnovation theory

Auxiliary model‐based multi‐innovation recursive identification algorithms for an input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity

Binarization plays an important role in document analysis and recognition (DAR) systems. In this paper, we present our winning algorithm in ICFHR 2018 competition on handwritten document image binarization (H-DIBCO 2018), which is based on background estimation and energy minimization. First, we adopt mathematical morphological operations to estimate and compensate the document background. It uses a disk-shaped structuring element, whose radius is computed by the minimum entropy-based stroke width transform (SWT). Second, we perform Laplacian energy-based segmentation on the compensated document images. Finally, we implement post-processing to preserve text stroke connectivity and eliminate isolated noise. Experimental results indicate that the proposed method outperforms other state-of-the-art techniques on several public available benchmark datasets.

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Lirong Li

Papers

An enhanced binarization framework for degraded historical document images

DP-LinkNet: A convolutional network for historical document image binarization