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5th International Conference on Computer Graphics, Imaging and Visualization (CGIV)

作者： Rahman, Wan Eny Zarina W. Abd. Ibrahim, Arsmah Abu Bakar, Zainab Mahmud, Rozi Salikin, Md Saion Manaf, Mazani Univ Teknol MARA Fac Informat Technol & Quantitat Sci Shah Alam 40450 Selangor Malaysia Univ Putra Malaysia Fac Med Serdang Malaysia Univ Teknol MARA Fac Hlth Sci Petaling Jaya Malaysia

ISBN: (纸本)9780769533599

Mammography is a known method for the early detection of breast cancer. However, the mammograms which are in black and white and in the shade of grey have some limitations in portraying the abnormalities. Image segmentation is a very crucial process in detecting abnormalities in computed radiography mammographic images. Active contours which are known as 'snake' are dynamic algorithms which can be used to perform the image segmentation. In order to test the applicability of the snake algorithm in performing segmentation, the breast phantom MRI-156 images are used. Only the breast phantom images at the exposures of 25 kV, 28 kV and 35 kV with milliampere (mAs) of 0.5 are considered. It is found that when the image is divided into four equal regions, the detection of abnormalities in the image is more effective as compared to the image processed as a whole.

关键词： Mammogram Segmentation snake algorithm Breast Phantom

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A Distributed snake algorithm for Mobile Robots Path Planning with Curvature Constraints

A Distributed Snake Algorithm for Mobile Robots Path Plannin...

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IEEE International Conference on System, Man, and Cybernetic

作者： Cheng, Y. Jiang, P. Hu, Y. Fun Univ Bradford Sch EDT Bradford BD7 1DP W Yorkshire England Univ Bradford Sch Informat Bradford BD7 1DP W Yorkshire England

ISBN: (纸本)9781424423835

Environment Intelligence is becoming ubiquitous. Wireless sensor networks supported environment intelligence is providing an opportunity to service robot navigation to reduce the complexity of conventional centralized and on-board map-building, localization, path-planning and motion control, whilst superior performance can be expected. In terms of robot path planning in a dynamic environment, distributed environment intelligence can take into account both global and local perceptions for path generation and adaptation, which results in better predictability and more prompt reaction. This paper proposes a snake based and distributed path planning algorithm for robot navigation in an intelligent environment with distributed wireless visual sensors. Via communication links between sensors, segments of a path, as an elastic band from start position to goal position, interact each other to react to repulsive forces from obstacles whilst maintain compliance. However, the compliance has to be subject to the robot kinematic constraints and the elastic hand may change to rigid or even to a broken state. A state machine is then presented to manage the state switch and control over the network. Simulations and experiments showed that the proposed distributed snake scheme can adapt to dynamic changes in the environment and satisfy the kinematic curvature constraints for the whole path.

关键词： robot navigation distributed path planning curvature constraints environment intelligence snake algorithm

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Automatic Mosaicking Method for Large Block of Orthophotos

Automatic Mosaicking Method for Large Block of Orthophotos

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7th Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Parallel Processing of Images and Optimization and Medical Imaging Processing

作者： Ai Haibin Zhang Li Wang Lin Chinese Acad Surveying & Mapping Beijing 100830 Peoples R China

ISBN: (纸本)9780819485793

In order to mosaic neighboring and partly overlapping orthophotos of a scene into one large image, the paper proposes a large block orthophoto mosaicking method. In our method, seam lines firstly are delineated through overlap areas among orthophotos according to an optimal geometrical criterion. Then a network of mosaicking is built based on these delineated seam lines, and related topology information may be easily abstracted from the mosaicking network. In the second stage of our method, each seam line is optimized again by a modified snake algorithm. The algorithm makes every seam line meet the requirements of maximum color similarity of the images and maximum texture similarity. In order to searching an optimal seam line in a large overlap area as fast as possible, a hierarchical strategy is adapted. In that way, an optimized path through the overlap area is found, where the color and texture of the two images are similar. The still remaining jumps in hue and the differences in intensity and saturation have to be leveled by smooth interpolation in the vicinity of the seam line. After having processed all overlapping areas, a large block of orthophotos are automatically merged to a final large image.

关键词： orthophoto mosaic topology network snake algorithm seamline detection

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Enhanced snake algorithm using the proximal edge search method

Enhanced snake algorithm using the proximal edge search meth...

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International Conference on Computational Science and Its Applications (ICCSA 2007)

作者： Cha, JeongHee Kim, GyeYoung Soongsil Univ Informat & Media Inst Sch Comp Sangdo 5 Dong Seoul South Korea

ISBN: (纸本)9783540744689

This paper proposes an enhanced snake algorithm using the proximal edge search method. The proposed algorithm adds a new energy term called "proximal edge search" to the existing greedy algorithm without any passive adjustment of weight. The new energy term is represented by the distance between the snake point and the edge when there is a proximal edge. This modified algorithm could improve the accuracy by acquiring the detailed contour of complex objects and actively resolve the passive determination of weight. The validity of the proposed method was proven through experiments.

关键词： proximal edge search snake algorithm greedy algorithm weight determination

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Detection of runway boundary in ATC ground radar

Detection of runway boundary in ATC ground radar

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2010 IEEE Radar Conference

作者： Pierucci, Laura Bocchi, Leonardo Univ Florence Dept Elect & Telecommun I-50139 Florence Italy

ISBN: (纸本)9781424458127

The radar environment is usually nonstationary and an efficient adaptation requires real-time exploitation of a priori knowledge concerning the environment surrounding the radar. In an airport contest, the radar scenario is heavily influenced by the inevitable presence of interferences, the background clutter, but other interferences (presence of vehicles and unwanted signs on the runway) contribute to make difficult the target detection. In particular, the paper addresses the detection of the runway boundary in ATC (Air Traffic Control) ground radar signal which can be not well defined due to the grass growth in different period in the islands near the runways. The grass growth can cause critical situation because the signal level of the grass zones is equal to that of the asphalt and it needs a visual analysis by a human operator to determine the presence of objects and targets in this clutter area. An active contour search algorithm (snake algorithm) is used for detecting the runway boundary in SMR radar images. In our application a standard snake algorithm is adapted and it is possible to obtain a reasonable approximation of the actual contour, which greatly reduces drawbacks related to the presence of the local minima. The performance of the active contour algorithm is tested on a set of radar images extracted from SMR radar images acquired in Italian airports.

关键词： clutter detection snake algorithm active contour

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Using PCA and LVQ Neural Network for Automatic Recognition of Five Types of White Blood Cells

Using PCA and LVQ Neural Network for Automatic Recognition o...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Tabrizi, P. R. Rezatofighi, S. H. Yazdanpanah, M. J. Univ Tehran Sch Elect & Comp Engn CIPCE Tehran Iran

ISBN: (纸本)9781424441242

Designing an effective classifier has been a challenging task in the previous methods proposed in the literature. In this paper, we apply a combination of feature selection algorithm and neural network classifier in order to recognize five types of white blood cells in the peripheral blood. For this purpose, first nucleus and cytoplasm are segmented using Gram-Schmidt method and snake algorithm, respectively;second, three kinds of features are extracted from the segmented areas. Then the best features are selected using Principal Component Analysis (PCA). Finally, five types of white blood cells are classified using Learning Vector Quantization (LVQ) neural network. The performance analysis of the proposed algorithm is validated by an expert's classification results. The efficiency of the proposed algorithm is highlighted by comparing our results with those reported in a recent article which proposed a method based on the combination of Sequential Forward Selection (SFS) as the feature selection algorithm and Support Vector Machines (SVM) as the classifier.

关键词： Gram-Schmidt method LVQ neural network PCA PCA neural network automatic cell recognition biomedical optical imaging blood cellular biophysics classification cytoplasm feature extraction feature extraction feature selection algorithm image classification image segmentation learning (artificial intelligence) learning vector quantization medical image processing neural nets nucleus peripheral blood principal component analysis principal component analysis segmentation sequential forward selection snake algorithm support vector machines support vector machines white blood cells

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A Framework for White Blood Cell Segmentation in Microscopic Blood Images Using Digital Image Processing

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BIOLOGICAL PROCEDURES ONLINE 2009年第1期11卷 196-206页

作者： Sadeghian, Farnoosh Seman, Zainina Ramli, Abdul Rahman Kahar, Badrul Hisham Abdul Saripan, M-Iqbal Department of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Department of Pathology Faculty of Medicine and Health Sciences Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Sapura Secured Technologies Section 10 Wangsa Maju Kuala Lumpur Malaysia

Evaluation of blood smear is a commonly clinical test these days. Most of the time, the hematologists are interested on white blood cells (WBCs) only. Digital image processing techniques can help them in their analysis and diagnosis. For example, disease like acute leukemia is detected based on the amount and condition of the WBC. The main objective of this paper is to segment the WBC to its two dominant elements: nucleus and cytoplasm. The segmentation is conducted using a proposed segmentation framework that consists of an integration of several digital image processing algorithms. Twenty microscopic blood images were tested, and the proposed framework managed to obtain 92% accuracy for nucleus segmentation and 78% for cytoplasm segmentation. The results indicate that the proposed framework is able to extract the nucleus and cytoplasm region in a WBC image sample.

关键词： White blood cell segmentation Active contours snake algorithm Zack thresholding

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Mobile target detection of intelligent surveillance system based on modified GVF

Mobile target detection of intelligent surveillance system b...

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4th International Conference on Computer Science and Education

作者： Zhou Jian-zhong Wang Shu-zong Naval Univ Engn Dept Weapon Engn Wuhan Peoples R China

ISBN: (纸本)9781424435197

the current methods of mobile target detection of video sequences have shortcomings such as poor disturbance-resistance and robustness. To solve this problem, an modified GVF snake algorithm was presented, new gradient vector field was founded which took full advantage of image gradient information, between-frame motion information and grey-level information of neighbor pixels. Simulation result indicates that this modified method can detect mobile target of video sequences efficiently, and improve the disturbance-resistance ability and robustness.

关键词： mobile target detection Gradient vector flow snake algorithm video sequences intelligent surveillance system

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Application of an Improved snake Model in Face Location Based on Skin-color

Application of an Improved Snake Model in Face Location Base...

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7th World Congress on Intelligent Control and Automation

作者： Huang Hanmin Jiang Zhen Chongqing Jiaotong Univ Sch Comp Sci Chongqing 400074 Peoples R China

ISBN: (纸本)9781424421138

In image processing and computer vision, snake (active contour model) is an effective tool in implementing brim detection or contour extraction of object. But the snake algorithm has the deadly shortcoming - the result is affected by the origin position. In this paper, proposed a new modified algorithm combining centric algorithm into the snake algorithm, so get the priority information of the origin position The algorithm reduces sensitivity to initialization while providing superior performance. Finally the results of the computer simulation show the advantage of the new algorithm.

关键词： face location face detection color space snake algorithm

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Design and implementation of gradient vector flow snake to detect a reference object in pelvic x-rays for preoperative total hip arthroplasty planning application

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JOURNAL OF DIGITAL IMAGING 2007年第4期20卷 373-380页

作者： Kristanto, W. van Ooijen, P. M. A. The, B. Duifhuis, H. Mengko, T. R. Oudkerk, M. Univ Med Ctr Groningen Dept Radiol NL-9700 RB Groningen Netherlands Univ Groningen Dept Biomed Engn NL-9700 RB Groningen Netherlands Inst Teknol Bandung Biomed Engn Elect Engn Dept Bandung 40132 Indonesia Univ Med Ctr Groningen Dept Orthoped NL-9700 RB Groningen Netherlands

The main interest of this research project is to promote automation in performing preoperative planning for hip joint replacement surgery using a special medical image viewing software, ViewPro (TM). Preoperative planning is performed to carefully prepare the surgery and to accurately select the hip implants. The first step of preoperative planning is to calibrate the x-ray image to adjust the magnification factor. A femoral head implant is used as magnification factor reference. Automation is introduced by developing an algorithm to automatically detect this reference object in the image. The algorithm used for performing the automatic detection of the reference object is gradient vector flow (GVF) snake. A study has been performed to compare the newly developed semiautomatic algorithm to the old manual calibration algorithm. The results show a close relation between the two algorithms (less than 1% of average relative difference). It is concluded that the developed semiautomated algorithm can be used as an alternative for performing the manual calibration.

关键词： preoperative planning total hip arthroplasty snake algorithm gradient vector flow

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