A fast algorithm for the restoration of images based on chain codes description and its applications

doi:10.1016/0734-189X(90)90149-P

Computer Vision, Graphics, and Image Processing

Volume 50, Issue 3, June 1990, Pages 296-307

Computer Vision, Gra...

https://doi.org/10.1016/0734-189X(90)90149-P Get rights and content

Abstract

A fast algorithm for the restoration of an image is presented. The image is described by using chain codes which record the contours of the image. The algorithm gives a simple idea for region filling. Some geometric properties for the image can be easily derived by our method. Comparison of the proposed method and one existing method is also provided.

References (12)

T Pavlidis
Filling algorithms for raster graphics
Comput. Graphics Image Process.
(1979)
Z Cai
Restoration of binary images using contour direction chain codes description
Comput. Vision Graphics Image Process.
(1988)
S.M Ali et al.
A new algorithm for extracting the interior of bounded regions based on chain coding
Comput. Vision Graphics Image Process.
(1988)
G.Y Tang
Region filling with the use of the discrete Green theorem
Comput. Vision Graphics Image Process.
(1988)
I.T Young et al.
An analysis technique for biological shape I
Inform. and Control
(1974)
B.D Ackland et al.
The edge flag algorithm—A fill method for raster scan display
IEEE Trans. Comput.
(1981)

There are more references available in the full text version of this article.

Cited by (20)

Flotation bubble seed image filling algorithm based on boundary point features
2012, International Journal of Mining Science and Technology
Citation Excerpt :
Therefore, it cannot avoid the under-filling and over-filling accurately. Chang improved Cai’s method and distinguished isolated points as singular and skipping points [5]. The major advantage of Chang’s algorithm over Cai is that it does not need to scan points out of the region, skip these isolated lines, and solve the over-filling problem partly.
Bubble seed image filling is an important prerequisite for the image segmentation of flotation bubble that can be used to improve flotation automatic control. These common image filling algorithms in dealing with complex bubble image exists under-filling and over-filling problems. A new filling algorithm based on boundary point feature and scan lines (PFSL) is proposed in the paper. The filling algorithm describes these boundary points of image objects by means of chain codes. The features of each boundary point, including convex points, concave points, left points and right points, are defined by the point’s entrancing chain code and leaving chain code. The algorithm firstly finds out all double-matched boundary points based on the features of boundary points, and fill image objects by these double-matched boundary points on scan lines. Experimental results of bubble seed image filling show that under-filling and over-filling problem can be eliminated by the proposed algorithm.
A new and fast contour-filling algorithm
2005, Pattern Recognition
Citation Excerpt :
But in the field of digital image processing, contour is usually described by chain codes [5,6] and thus, its filling algorithm [7–11] is very different from that in computer graphics field. Algorithms in [7–9] comply with the principle of parity check by analyzing the attributes of the contour pixels’ chain code, classifying contour points into isolated points, marking points, and skipping points. The isolated points and skipping points are temporarily neglected during the filling in order to present the occurrence of the wrong number of line segments.
Contour filling is one of the most common problems in image and graphics processing. The executing speed of the contour filling is vital, especially for a real-time system. This paper studies the advantages and disadvantages of the conventional filling algorithms, analyzes their original ideas, and proposes a new filling algorithm. The new algorithm presents a very simple idea for finding seeds automatically, and limits the scan within the filling regions. Repeated experiments have proven that with the new algorithm, any complex inner and outer contours can be filled with higher speed.
A parallel algorithm for generating chain code of objects in binary images
2003, Information Sciences
This paper addresses parallel execution of chain code generation on a linear array architecture. The contours in the proposed algorithm are viewed as a set of edges (or contour segments) that can be traced by a top-down contour tracing method to generate the chain codes for the outer and inner object contours. A parallel algorithm that contains the chain code generating rules and operations needed is also described, and the algorithm is mapped onto a one-dimensional systolic array containing $⌈ 12 (N+1)⌉$ processing elements (PEs) to devise this architecture. The architecture extracts the contours of objects and quickly generates the corresponding chain codes after the image data in all rows are inputted in a linear fashion. The total processing time for generating the chain codes in an N×N image is O(3N). By doing so, the real-time requirement is fulfilled and its execution time is independent of the image content. In addition, a partition method is developed to process an image when the parallel architecture has a fixed number of PEs; say two or more. The total execution time for an N×N image by employing a fixed number of PEs is N(N+1)/M+2(M−1), when M is the fixed number of PEs.
Tracing boundary contours in a binary image
2002, Image and Vision Computing
This paper presents a new contour tracing algorithm for tracing boundary contours in a 2D binary image, which plays a very important role in digital image processing, pattern recognition and machine vision system. The new algorithm has three main advantages compared to existing algorithms. First, it never loses inner boundaries of arbitrary complicated regions. Second, it preserves space connectivity. Third, the algorithm is faster on implementation. These advantages are proved in theory and experiments.
Representation of segmented images with discrete geometric maps
1999, Image and Vision Computing
Most models of representation of a segmented image have been designed to perform specific processing on images and are generally ill-adapted to other processes. Moreover, usually models describe separately the geometry and the topology of the regions of the image. Generally, this dichotomy makes it difficult or costly to design and implement operations involving both topological and geometrical features. In this paper, we give a complete description of a model encoding both geometry and topology of the region's of a segmented image. This model, based on inter-pixel boundaries associated with topological planar maps, has been successfully used for image segmentation.
Reconstruction of binary and gray-scale images from mid-crack code descriptions
1993, Journal of Visual Communication and Image Representation
The chain code is a widely-used description for a contour image. Recently, a mid-crack code algorithm has been proposed as another more precise method for image representation. A simple and fast algorithm for the restoration of binary images based on mid-crack codes description is presented in this paper. The algorithm developed has the advantages of speed, simplicity, and less storage. The algorithm also can be applied to gray-scale images with multiple regions efficiently.

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A fast algorithm for the restoration of images based on chain codes description and its applications

Abstract

Comput. Graphics Image Process.

Comput. Vision Graphics Image Process.

Comput. Vision Graphics Image Process.

Comput. Vision Graphics Image Process.

Inform. and Control

The edge flag algorithm—A fill method for raster scan display

IEEE Trans. Comput.