A new method for image segmentation
01 Nov 2009-Vol. 2, pp 123-125
TL;DR: A new segmentation method which is based on the morphology method, fuzzy K-means algorithm and some parts operator of the Canny algorithm, and the course of Canny operator that calculating the value and direction of grads, non-maxima suppression to the grad value and lag threshold process into the post-treatment process is introduced.
Abstract: On the basis of analyzing the blur images with noise, this paper presents a new segmentation method which is based on the morphology method, fuzzy K-means algorithm and some parts operator of the Canny algorithm. Because of the Canny's good performance on good detection, good localization and only one response to a single edge, we introduce the course of Canny operator that calculating the value and direction of grads, non-maxima suppression to the grad value and lag threshold process into our post-treatment process. Through experiments, it is demonstrated that the image segmentation method in this paper is very effective.
Citations
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01 Jan 2013
TL;DR: The proposed contrast based thresholding method for old degraded manuscript images is an approach for degraded manuscript and document images by introducing an estimation of the threshold value that effectively segments the texts from badly degraded document background.
Abstract: Thresholding is an essential procedure used in image segmentation and binarization applications. In this paper, segmentation methods applied on document images for separating the text from background presents pure binarization and filtering combined with image processing algorithms. This paper describes a contrast based thresholding method for old degraded manuscript images. It is an approach for degraded manuscript and document images by introducing an estimation of the threshold value. This technique effectively segments the texts from badly degraded document background. The method is suitable for segmentation of document images with complex and uneasy background having unreadable text. Proposed method performs segmentation using contrast estimating a threshold and exhaustively uses discrete gray level values. The proposed method broadly evaluated on more than 100 degraded manuscript images. The result shows the readable text in the improved images produced by the proposed method. Experiments confirm the effectiveness of the proposed method compared to standard thresholding methods. In research, the proposed method produced better results than standard thresholding methods for original manuscript images.
6 citations
Cites methods from "A new method for image segmentation..."
...The method in [5] creates a threshold surface to find exact object boundaries for local threshold values using a gradient map of the image....
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02 Mar 2021
TL;DR: Zhang et al. as mentioned in this paper proposed PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China and Shenzhen Bay Laboratory, Shenzhen 518055, China.
Abstract: Molecular Medicine, Peking University, Beijing 100871, China. 11 PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China. 12 School of Mathematical Sciences, Peking University, Beijing 100871, China. 13 Biomedical Engineering Department, Peking University, Beijing 100191, China. 14 Shenzhen Bay Laboratory, Shenzhen 518055, China. 15 School of Software and Microelectronics, Peking University, Beijing 100871, China. 16 Institute for Brain Research and Rehabilitation (IBRR), Guangdong Key Laboratory of Mental Health and Cognitive Science, 17
6 citations
DOI•
01 Jan 2017
TL;DR: This document summarizes current capabilities, research and operational priorities, and plans for further studies that were established at the 2015 USGS workshop on quantitative hazard assessments of earthquake-triggered landsliding and liquefaction in the Czech Republic.
Abstract: ........................................................................................................................................... 5 Zusammenfassung........................................................................................................................... 7
6 citations
TL;DR: This paper observes the possibility of volume estimate of mango using image processing technique that are used in commercial packaging industry for increase the quality of fruits.
Abstract: This paper observes the possibility of volume estimate of mango using image processing technique that are used in commercial packaging industry for increase the quality of fruits. Image processing is used to provide automation and cost-effective service to packaging industry for volume estimation of mango. Sizes featured are extracted from digit profile image using many image processing technique. The volume of fruit is obtained using single or multiple camera setups. The sizes featured are used to estimated volume of mango and compare with actual volume of mango. That program can measure the size property of mango such as height, width and area from image but there is one problem is that the size feature of mango is not accurate. We have to done some changes to achieve high accuracy of size featured of mango.
6 citations
DOI•
01 Jan 2009
TL;DR: In this article, the authors present an automatic method that allows numismatists to faster and more accurately process top view photographs of ancient coins with a ruler placed next to the coin.
Abstract: Museums catalogue their ancient coins using top view photographs in which a ruler is placed next to the coin. We present an automatic method that allow numismatists to faster and more accurately process such images. The method consists of two parts. The first part uses a novel algorithm to calculate the images’ scale by a Fourier analysis of the characteristic pattern produced by the ruler. Therefore, distances can be measured in terms of the units on the ruler. The second part uses a shape-adaptive thresholding method to isolate the coin from the background. This makes it possible to determine the real-world size of the coin. Experimental results on 30 images show the high accuracy and robustness of the two algorithms with respect to different coins and rulers as well as the ruler's orientation, position and size.
6 citations
References
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TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Abstract: This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal assumptions about the form of the solution. We define detection and localization criteria for a class of edges, and present mathematical forms for these criteria as functionals on the operator impulse response. A third criterion is then added to ensure that the detector has only one response to a single edge. We use the criteria in numerical optimization to derive detectors for several common image features, including step edges. On specializing the analysis to step edges, we find that there is a natural uncertainty principle between detection and localization performance, which are the two main goals. With this principle we derive a single operator shape which is optimal at any scale. The optimal detector has a simple approximate implementation in which edges are marked at maxima in gradient magnitude of a Gaussian-smoothed image. We extend this simple detector using operators of several widths to cope with different signal-to-noise ratios in the image. We present a general method, called feature synthesis, for the fine-to-coarse integration of information from operators at different scales. Finally we show that step edge detector performance improves considerably as the operator point spread function is extended along the edge.
28,073 citations
"A new method for image segmentation..." refers methods in this paper
...Canny operator[2] transforms the edge detection problem into the problem of unit function maximum detection....
[...]
TL;DR: This work presents a simple and efficient implementation of Lloyd's k-means clustering algorithm, which it calls the filtering algorithm, and establishes the practical efficiency of the algorithm's running time.
Abstract: In k-means clustering, we are given a set of n data points in d-dimensional space R/sup d/ and an integer k and the problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. A popular heuristic for k-means clustering is Lloyd's (1982) algorithm. We present a simple and efficient implementation of Lloyd's k-means clustering algorithm, which we call the filtering algorithm. This algorithm is easy to implement, requiring a kd-tree as the only major data structure. We establish the practical efficiency of the filtering algorithm in two ways. First, we present a data-sensitive analysis of the algorithm's running time, which shows that the algorithm runs faster as the separation between clusters increases. Second, we present a number of empirical studies both on synthetically generated data and on real data sets from applications in color quantization, data compression, and image segmentation.
5,288 citations
"A new method for image segmentation..." refers methods in this paper
...Fuzzy K-means algorithm[3] that divides the samples on various categories of membership according to the data is a clustering method in more common use....
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Book•
15 Sep 1994
TL;DR: The fundamental principles of Digital Image Processing are explained, as well as practical suggestions for improving the quality and efficiency of image processing.
Abstract: What Is Image Processing?. Fundamentals of Digital Image Processing. The Digital Image. PROCESSING CONCEPTS. Image Enhancement and Restoration. Image Analysis. Image Compression. Image Synthesis. PROCESSING SYSTEMS. Image Origination and Display. Image Data Handling. Image Data Processing. PROCESSING IN ACTION. Image Operation Studies. Appendices. Glossary. Index.
457 citations
12 May 1998
TL;DR: A novel method for measuring the orientation of an edge is introduced and it is shown that it is without error in the noise-free case, and the wreath product transform edge detection performance is shown to be superior to many standard edge detectors.
Abstract: Wreath product group based spectral analysis has led to the development of the wreath product transform, a new multiresolution transform closely related to the wavelet transform. We derive the filter bank implementation of a simple wreath product transform and show that it is in fact, a multiresolution Roberts (1965) Cross edge detector. We also derive the relationship between this transform and the two-dimensional Haar wavelet transform. We prove that, using a non-traditional metric for measuring edge amplitude with the wreath product transform, yields a rotation and translation invariant edge detector. We introduce a novel method for measuring the orientation of an edge and show that it is without error in the noise-free case. The wreath product transform edge detection performance is shown to be superior to many standard edge detectors.
19 citations