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Detecting Mango Fruits by using Randomized Hough Transform and Backpropagation Neural Network 18

Detecting Mango Fruits by using Randomized Hough Transform a...

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18th International Conference on Information Visualisation (IV)

作者： Nanaa, Kutiba Rizon, Mohamed Abd Rahman, Mohd Nordin Ibrahim, Yahaya Abd Aziz, Azim Zaliha Univ Sultan Zainal Abidin UniSZA Fac Informat & Comp Kuala Lumpur Terengganu Malaysia Univ Sultan Zainal Abidin UniSZA Fac Design & Engn Technol Kuala Lumpur Terengganu Malaysia Univ Sultan Zainal Abidin UniSZA Fac Appl Social Sci Kuala Lumpur Terengganu Malaysia

ISBN: (纸本)9781479941032

A new method for mango detection is presented in this paper. This method is based on preprocessing operators on image which includes converting to gray image, finding edges, calculating distances to edges, opening morphology and converting to binary color image. To take advantage of oval shaped mango fruit, we apply Randomized Hough Transform method to detect potential places for mango fruit in input images. By using Backpropagation Neural Network, we recognize mango fruits from these potential places. The dataset used to implementing this paper is 50 RGB images captured of mango fruits on trees. As shown in experimental results, in the case of clear fruit in input images, the detection rates up to 96.26% while it decreases in the case of partially covering or overlapping. However, this method can be applied to detect other fruits in varied sizes and colors.

关键词： Detecting Mango image recognition feature extraction image segmentation neural network watershed algorithm Randomized Hough Transform detecting Fruits

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Detection of tumor region in MR image through fusion of Dam construction and K-mean clustering algorithms 2

Detection of tumor region in MR image through fusion of Dam ...

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2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)

作者： Faris, Muhammad Javid, Tariq Fatima, Kashaf Azhar, Maliha Kamran, Rohana Hamdard Univ Dept Biomed Engn Fac Engn Sci & Technol Karachi Pakistan

ISBN: (纸本)9781538695098

The Brain is the major central monitoring region of the human nervous system. Tumor growth is a speedy and abandoned growth of unhealthy cells of the brain. Magnetic Resonance Imaging (MRI) is the method frequently used to identify tumor region in the brain. Usually, MR images are not that much appropriate for comprehensive examination, because of this reason medical image treating is one of the most significant, demanding and rising field during this era of modern medical technology. The fundamental goal of this proposed technique is to highlight the borders of tumor area. This research technique is based upon three major tasks filtration, Edge preservation, and Segmentation. For this purpose first step is to remove 'salt and pepper' noise from MR scan by applying median filter because of the efficiency, then preserve the edges in order to enhance the borders of tumor region. For this operation combination of two edge operators `Sobel and Canny' are used to design hybrid edge operator and display all the entities present in MR scan. Segmentation is one of the most important techniques required to evaluate and diagnose the brain tumor. Segmentation techniques are used to split an image in multiple regions. In segmentation pixels are labeled with same characteristics many different methods are used for segmentation of medical images just like C-means clustering, K-means clustering, region merging, region splitting and watershed segmentation etc. This proposed technique is the combination of three major segmentation approaches 'K-means clustering, watershed algorithm and Otsu binarization. This paper has displayed the contrast between all techniques at each step and also implemented the hybridized result by extracting tumor region in MR image. Results have compared and evaluated on the basis of different image parameters like MSE and PSNR, etc.

关键词： MR scan Noise Median filter Edge operator hybridization watershed algorithm K-means clustering Otsu binarization

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Interactive Image Segmentation Based on Grow Cut of Two Scale Graphs

Interactive Image Segmentation Based on Grow Cut of Two Scal...

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9th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2012

作者： Li, Xiaoqiang Chen, Jingsong Fan, Huafu Shanghai Univ Shool Comp Engn & Sci Shanghai Peoples R China Zhoukou Normal Univ Dept Math & Informat Sci Zhoukou Peoples R China

ISBN: (纸本)9783642345944

This paper proposes a novel interactive image segmentation algorithm based on the Grow Cut of two different scale graphs. Firstly, watershed algorithm based on color information has been used to partition the image into many different regions which will be considered as the cells of Grow Cut, instead of image pixels. Then a segmentation result can be obtained by using Grow Cut on the aforementioned regions. Finally an automatic edge correction can be used on the segmentation result by Grow Cut of pixel-scale graph. Because the number of nodes and edges for the Grow Cut algorithm is reduced by more than fifty times compared to the pixel based method, the running time of our proposed algorithm is much less than the original Grow Cut. The segmentation performance of our proposed is much better than the original Grow Cut. Experimental results on Berkeley image dataset demonstrated the effectiveness of proposed method.

关键词： Image segmentation Grow Cut watershed algorithm Automatic Edge Correction

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A Novel Neural Network Based Automated System for Diagnosis of Breast Cancer from Real Time Biopsy Slides

A Novel Neural Network Based Automated System for Diagnosis ...

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International Conference on Circuits, Communication, Control and Computing (I4C)

作者： Singh, Seema Harini, J. Surabhi, B. R. BMS Inst Technol Dept Elect & Commun Bangalore Karnataka India

ISBN: (纸本)9781479965458

Breast cancer is one of fatal disease in women, which is better curable if detected at an early stage. This paper presents a neural network based diagnosis system for breast cancer. Neural network system has the ability to be trained by large data and hidden information or features in the samples. Thus exhaustive case studies of a specialized doctor can be used to train a neural network which results in an efficient decision making tool in field of cancer diagnosis. Artificial neural network (ANN) based diagnostic system for breast cancer is developed using two stages. Firstly, the well-known Wisconsin Breast Cancer Database (WDBC) is used to develop the diagnostic system. Supervised training of neural network using back propagation algorithm is done. Two variants of back propagation algorithm are investigated with three and four layers of neural networks. With efficient neural network developed, the tested method is applied for biopsy slide images of breast tissues. Preprocessing of images is done to extract required key features using image processing algorithms using Matlab Simulink. Thus a data set is created using the case studies of breast cancer cases. This work demonstrated that neural network can be an efficient decision making tool in field of cancer diagnosis using biopsy slides.

关键词： Breast cancer biopsy slides watershed algorithm neural networks back propagation Simulink

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Adaptive centroid optimization for Shack-Hartmann wavefront sensor

Adaptive centroid optimization for Shack-Hartmann wavefront ...

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International Conference on Optical Instruments and Technology (OIT) - Optoelectronic Imaging and Processing Technology

作者： Gan, Jinrui Jing, Wenbo Wang, Xiaoman Changchun Univ Sci & Technol Coll Optoelect Engn Changchun 130022 Peoples R China Changchun Univ Sci & Technol Coll Elect & Informat Engn Changchun 130022 Peoples R China

ISBN: (纸本)9780819499639

The accuracy of the Shack-Hartmann wavefront sensor (SHWS) for measuring the distortion wavefront is mainly dependent upon the measurement accuracy of the centroid of the focal spot. Many methods have been presented to improve the accuracy of the wavefront centroid measurement, but most of them are based on a point of improvement. Propose a complete centroid optimization method. Based on analyzing background noise of the focal spot image, the method of adaptive threshold denoising is introduced, then the sub-aperture detection windows are optimized by modified watershed algorithm, and the centroid of the focal spot is calculated by the higher moment centroid algorithm in an optimized window, where the linear interpolation have been used. Simulation and experimental results showed that the centroid detection window could automatically adjust its size, matching perfect with spot distribution area, and the proposed method could reach high precision and repeatability of focal spot centroid in some certain SNR.

关键词： SHWS centroid detection error adaptive threshold watershed algorithm linear interpolation

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An improved algorithm for shot cut detection

An improved algorithm for shot cut detection

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Conference on Visual Communications and Image Processing 2005

作者： Hashimah, PN Gao, L Qahwaji, R Jiang, JM EIMC Dept Bradford W Yorkshire England

ISBN: (纸本)0819459763

The increasing availability and use of online video has led to a high demand for very accurate and efficient automated video analysis techniques. Previous research has concentrated on segmenting videos by detecting the boundaries between camera shots. Shot cut detection is the first step in every video indexing and retrieval algorithm. A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. However, there is no dataset that is internationally agreed upon to be used as a benchmark for evaluating the emerging techniques. In this paper, a new algorithm is proposed for the shot cut detection. The detection algorithm consists of three major stages. The morphological Hit-Miss transform is applied in the first stage. The watershed transform is applied next and finally feature extraction is carried out. To enable comparison with previous work, the dataset used in this new algorithm is applied to the technique introduced by T. Y. Liu et al.,2004. Our algorithm shows a remarkable difference and it provides a better recall and precision rates.

关键词： watershed algorithm shot cut detection Hit-Miss Transform MPEG video sequence

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Classification Method Research of Fresh Agaricus Bisporus Based on Image Processing 11th

Classification Method Research of Fresh Agaricus Bisporus Ba...

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11th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture (CCTA)

作者： Wang, Fengyun Zheng, Jiye Wang, Lei Feng, Wenjie Niu, Luyan Shandong Acad Agr Sci S&T Informat Inst Jinan 250100 Shandong Peoples R China

ISBN: (纸本)9783030061371;9783030061364

The article studies the classification method for the fresh agaricus bisporus based on image processing. When acquiring the image information, the shadow of image and mushroom stipe may affect the analysis of maximum diameter of agaricus bisporus which is the important factor. In this paper, the global threshold segmentation method and maximum entropy threshold segmentation method are combined to carry out the first watershed algorithm to remove the shadow of image. Then the Canny operator, opening and closing operation and corrosion expansion are used to carry out the second watershed algorithm for the removal of stipe interference. The method achieves a good result through the comparison between the actual measured results and experimental results.

关键词： Agaricus bisporus Image processing Maximum entropy threshold segmentation watershed algorithm

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Stereoscopic video object segmentation based on depth and edge information

Stereoscopic video object segmentation based on depth and ed...

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International Conference on Photoelectronic Detection and Imaging

作者： Lue Chaohui Yuan Dun Zhang Qin Commun Univ China Sch Informat Engn Beijing 100024 Peoples R China

ISBN: (纸本)9780819467676

An effective scheme for stereoscopic video object segmentation was presented based on depth and edge information. Disparity estimation algorithm using region information was firstly proposed to get reliable depth information. In. the proposed method, a new adaptive-size window approach was introduced to stereo matching in order to overcome problems with fixed-size window. Then, an improved watershed algorithm was exploited to achieve initial segmentation of depth image and coarse object areas were obtained. For each depth segments, edge detection was implemented to obtain accurate contours of object. Finally, watershed algorithm was utilized to segment object again. Using the extracted objects, an efficient motion tracking algorithm based on region was performed to track the video objects of the rest frames. The experimental results show that the proposed method can get good disparity map and segment video objects successfully.

关键词： stereoscopic video object segmentation disparity estimation watershed algorithm edge detection

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Image segmentation algorithm for location of laser spots during aircraft relative attitude determination

Image segmentation algorithm for location of laser spots dur...

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6th International Symposium on Precision Engineering Measurements and Instrumentation

作者： Hou, Binke Ding, Xuemei Harbin Inst Technol Inst Ultraprecis Opt & Elect Instrument Engn Harbin 150001 Peoples R China

ISBN: (纸本)9780819479402

An image segmentation method is proposed to locate the position of laser spots reflected by corner-cube array during relative attitude determination between aircrafts. First, the laser spots image acquired by CCD camera is transformed to a grayscale gradient distribution image by the Roberts operator. Then the image is divided into several small pieces according to the distribution of both energy and grayscale gradient. Each piece is segmented based on watershed algorithm individually to detect the margin of laser spots. Seeds of watershed segmentation are selected by using prior knowledge of appearance and energy of laser spots predicted when the laser measure system is designed. A binary image which contains the edge information of the laser spots is acquired after all segmented pieces is merged together. Then expansion and erosion algorithm is used to reduce the effect of over segmentation. The method can effectively remove the system noise or the disturbance brought by the reflection of the other optical antenna near the corner-cube array on the client terminal. Experimental results indicate that location of laser spots calculated by centric method is exactly limited in the anticipated area. The uncertainty of the center location is no more than 1 pixel.

关键词： relative attitude watershed algorithm grayscale threshold over-segmentation

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An automatic detection of the retinopathy of prematurity demarcation-line/ridge on infant retinal images.

An automatic detection of the retinopathy of prematurity dem...

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IEEE Region 10 Conference on Analog and Digital Techniques in Electrical Engineering

作者： Sinthanayothin, C Barman, S National Electronics and Computer Technology Center Thailand Digital Imaging Research Centre Kingston University United Kingdom

ISBN: (纸本)0780385608

The purpose of this research was to present an image processing tool in order to provide ophthalmologists with assistance for diagnosis. This work has been developed to automate detection of the retinopathy of prematurity demarcation line or ridge pattern which is mainly used to determine the progress of the over production of blood vessels in the eye. The techniques presented in this paper consist of 4 main steps. First a local contrast enhancement has been applied and followed with a large filter based on Canny edge detection. Then an algorithm is applied based on an image processing technique called an early stopping watershed Finally, some region classification techniques are applied to the infant images. The watershed technique in this research is differs from the general watershed technique, because a gradient image is used as input data instead of gray scale or a thresholded image. Also in the algorithm used, the area, which has intensity equal to zero was automatically set as the initial seed points and stopped at particular level dependent on the variance of the whole image. The results obtained from application of the watershed algorithm were assessed for the possibility of being ROP ridge regions. The areas exhibiting a high probability of being an ROP ridge region were extracted using a region classification technique and exhibited to the clinician as a second decision.

关键词： retinopathy of prematurity local contrast enhancement watershed algorithm regions classification

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