Broken Character Image Restoration Using Genetic Snake Algorithm: Deep Concavity Problem

Qusay Omran Mosa,Mohammad Faidzul Nasrudin

doi:10.3844/jcssp.2016.81.87

Qusay Omran Mosa, Mohammad Faidzul Nasrudin

Open Access

https://doi.org/10.3844/jcssp.2016.81.87

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Abstract

Active contours also known as snakes became a familiar and widely used in the field of image segmentation and restoration of historical documents in last few decades. Gradient Vector Flow (GVF) snake successes in overcome of converge to boundary concavities which represents the drawback of traditional snakes. Deep concavity problem it has become Obstacle faced GVF snake when restoring broken characters of historical documents. In this study we proposed algorithm to use genetic algorithm with GVF snake algorithm in order to optimize snake points to get right positions in deep concavity boundaries, also adding a Divergence factor as the third force to enhance the restoring and recognizing results. The experimental results show that our proposed algorithm has more capture than GVF alone.

Highlights

Old documents have important information converted to digital images to save it from degradation
We evaluate the proposed algorithm on restored broken characters which have complex object with deep boundaries concavities already Gradient Vector Flow (GVF) snake algorithm had suffered from lack converge it
Genetic optimized for GVF was able to optimize the positions of snake points direct to deep boundary concavities adopted on maximize of fitness function which produced from minimization of energy forces and divergence

Summary

Introduction

Old documents have important information converted to digital images to save it from degradation. Most of these documents suffer from degradation like humidity, storing environments, ink, washed water. Active contours (snakes) are the efficient methods used in image segmentations to detect boundaries of images. Drawbacks in traditional snakes like initializing snake curve and converge to concave areas led to update new techniques be able to access concave object boundaries. GVF have large capture range and ability of converge to concave boundaries, it is difficult torealize accurate segmentation to detect deep concavities of complex shapes. Thepurpose of this paper is to overcome deep concavity problem by optimizing GVF snake points to deep concavity boundaries using genetic algorithm.

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Materials and Methods

Conclusion