2013•Applied Mechanics and MaterialsRequires access

A Simple Hole Filling Algorithm for Binary Cell Images

Hang Zhao, Zhao Xue Chen

Open publisher page 6 citations

Abstract

Filling holes in binary images is often required during medical image processing and analysis. However, traditional hole filling algorithms for medical images expose some disadvantages such as possible edge degradations and relatively low efficiency. To overcome such limits, a hole filling algorithm for binary cell images based on largest connected region extraction is proposed in this paper. Since there are less pixels for foreground areas in usual binary cell images, the holes in the binary images can be simply filled by extracting & filling the largest connected region in correspondent negative images together with a following OR operation between the obtained result image and the original binary image. Such an algorithm based on largest connected region extraction nearly has no effect on edge information of the ROI(region of interested) with high accuracy and efficiency. The final experiments show its validity and advantage over the traditional morphology methods for hole filling in binary cell images. Thus the presented method is of a considerable reference value for binary image processing.

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What this paper is about

Filling holes in binary images is often required during medical image processing and analysis. However, traditional hole filling algorithms for medical images expose some disadvantages such as possible edge degradations and relatively low efficiency. To overcome such limits, a hole filling algorithm for binary cell images based on largest connected region extraction is proposed in this paper. Since there are less pixels for foreground areas in usual binary cell images, the holes in the binary images can be simply filled by extracting & filling the largest connected region in correspondent negative images together with a following OR operation between the obtained result image and the original binary image. Such an algorithm based on largest connected region extraction nearly has no effect on edge information of the ROI(region of interested) with high accuracy and efficiency. The final experiments show its validity and advantage over the traditional morphology methods for hole filling in binary cell images. Thus the presented method is of a considerable reference value for binary image processing.

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Available abstract

Filling holes in binary images is often required during medical image processing and analysis. However, traditional hole filling algorithms for medical images expose some disadvantages such as possible edge degradations and relatively low efficiency. To overcome such limits, a hole filling algorithm for binary cell images based on largest connected region extraction is proposed in this paper. Since there are less pixels for foreground areas in usual binary cell images, the holes in the binary images can be simply filled by extracting & filling the largest connected region in correspondent negative images together with a following OR operation between the obtained result image and the original binary image. Such an algorithm based on largest connected region extraction nearly has no effect on edge information of the ROI(region of interested) with high accuracy and efficiency. The final experiments show its validity and advantage over the traditional morphology methods for hole filling in binary cell images. Thus the presented method is of a considerable reference value for binary image processing.

Key concepts: Binary image, Binary number, Image (mathematics), Enhanced Data Rates for GSM Evolution, Pixel, Image processing, Computer science, Algorithm

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