• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.75-80
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• 2016

The process of extracting external boundary of an object is a very important process for recognizing an object in the image. The proposed extraction method consists of two processes: External Boundary Extraction and Thinning. In the first step, external boundary extraction process separates the region representing the object in the input image. Then, only the pixels adjacent to the background are selected among the pixels constituting the object to construct an outline of the object. The second step, thinning process, simplifies the outline of an object by eliminating unnecessary pixels by examining positions and interconnection relations between the pixels constituting the outline of the object obtained in the previous extraction process. As a result, the simplified external boundary of object results in a higher recognition rate in the next step, the object recognition process.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.5
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• pp.775-783
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• 1990

In this paper we implemented the fast thinning unit by modifying the pipeline architecture which was proposed by Stanley R. Sternberg. The unit is useful in preprocessing such as image representation and pattern recognition etc. This unit is composed of interface part, local memory part, address generation part, thinning processing part and control part. In thinning processing part, we shortened the thinning part which performed by means of look up table using window mapping table. Thus we improved the weakness of SAP, in which the number of delay pipeline and window pipeline are equal to image column size. Two independent memorys using tri-state buffer enable the two direction flow of address generated by address generation part. This unit avoids the complexity of architecture and has flexibility of image size by means of simple modification of logic bits.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.60.2-60
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• 2001

In this paper, manufacturing system and Internet are combined and NC milling machine engraves image and text on nameplate. Image and text are input through Internet. And NC tool path is obtained by thinning algorithm and NC part program is generated. Thinning algorithm detects center lines from image and text by using connectivity and tool path is obtained along the center line. Actually experiments are performed and thinning algorithm and G-code generation module are verified.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.73-81
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• 2004

To extract the creditable features in fingerprint image, many people use the thinning algorithm that has a very important position in the preprocessing. In this paper, we propose the robust parallel thinning algorithm that can preserve the connectivity of the binarized fingerprint image, make the thinnest skeleton with 1-pixel width and get near to the medial axis extremely. The proposed thinning method repeats three sub-iterations. The first sub-iteration takes off only the outer boundary pixel by using the interior points. To extract the one side skeletons, the second sub-iteration finds the skeletons with 2-pixel width. The third sub-iteration prunes the needless pixels with 2-pixel width existing in the obtained skeletons and then the proposed thinning algorithm has the robustness against the rotation and noise and can make the balanced medial axis. To evaluate the performance of the proposed thinning algorithm we compare with and analyze the previous algorithms.

• IE interfaces
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• v.15 no.1
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• pp.20-25
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• 2002

In this research, a nameplate engraving system for images and texts downloaded through Internet on nameplate is developed. The system consists of two subsystems: thinning algorithm and NC code generation module. In the thinning algorithm, the concept of connectivity is used and center lines of images and texts, which will be used as NC tool paths, can be obtained successfully. Because the center lines are composed of a lot of pixels, NC code would be too long. In the NC code generation module, many useless pixel data are removed and linear interpolation algorithm is applied to only the remaining pixels. By performing actual experiments, the thinning algorithm and the NC code generation module are verified.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2816-2822
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• 1999

In this paper, a fast thinning method for fingerprint image by separating end and bifurcation region is proposed. To detect feature points in automatic fingerprint identification system, thinning of fingerprint is essential. The end and bifurcation regions in ridge line are separated by means of run-length coding, and parallel thinning method is applied to the separated regions. The rest parts except the end and bifurcation regions are processed by connecting center points of each run. The performance of the proposed method has been evaluated by CPU processing time and thinness measurement. By the experimental results, the proposed method is fast and has high thinness value.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.35-43
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• 1992

We have presented the tracing algorithm for center pixel of character image. Character image was read by scanner device. Performing the tracing process, it can be possible to detect feature points, such as branch point, stroke of 4 directions. So, the tracing process covers the thinning and feature point detection process for improving the processing time. Usage of suggested tracing algorithm instead of thinning that is the preprocessing of character recognition increases speed up to 5 times. The preprocessing chip has been designed by using single layer perceptron algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.96-104
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• 1998

A new gray-scale thinning algorithm using local min/max operations is proposed. In this method, erosion and dilation properties of local min/max operations are using for generating new rides and detecting ridges in gray scale image, and gray-scale skeletons are gradually obtained by accumulating the detected ridges. This method can be applicable to the unsegmented image in which object are not specified, and the obtained skeletons correspond to the ridges (high gray values) of an input image.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.570-574
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• 2010

A thinning algorithm changes a binary fingerprint image to one pixel width. A thinning stage occupies 40% cycle of 32-bit RISC microprocessor system for a fingerprint identification algorithm. Hardware block processing is more effective than software one in speed, because a thinning algorithm is iteration of simple instructions. This paper describes an effective hardware scheme for thinning stage processing using the Verilog-HDL in $160\times192$ Pixel Array. The ZS algorithm was applied for a thinning stage. The hardware scheme was designed and simulated in RTL. The logic was also synthesized by XST in FPGA environment. Experimental results show the performance of the proposed scheme.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.315-324
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• 1996

This study was one of a series of studies on application of machine vision and image processing to extract the geometrical features of plants and to analyze plant growth. Several algorithms were developed to measure morphological properties of plants and describing the growth development of in-situ lettuce(Lactuca sativa L.). Canopy, centroid, leaf density and fractal dimension of plant were measured from a top viewed binary image. It was capable of identifying plants by a thinning top viewed image. Overlapping the thinning side viewed image with a side viewed binary image of plant was very effective to auto-detect meaningful nodes associated with canopy components such as stem, branch, petiole and leaf. And, plant height, stem diameter, number and angle of branches, and internode length and so on were analyzed by using meaningful nodes extracted from overlapped side viewed images. Canopy, leaf density and fractal dimension showed high relation with fresh weight or growth pattern of in-situ lettuces. It was concluded that machine vision system and image processing techniques are very useful in extracting geometrical features and monitoring plant growth, although interactive methods, for some applications, were required.