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An anatomization of noise removal techniques on medical images

An anatomization of noise removal techniques on medical imag...

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International conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH)

作者： Madhulika Pandey Madhulika Bhatia Abhay Bansal Computer Science and Engineering Department Amity University Noida India

ISBN: (纸本)9781509020850

In applications of signal processing such as medicine, communications and satellites, preprocessing is considered as a vital step which focuses on reduction or removal of the level of the noise contained in the image. The process of denoising helps in preserving the finer details and useful information. Medical images like MRI, CT and X-ray contain very fine details that need to be correct and free from noise so that the information and features of interests are not lost during the diagnosis. In this paper, various noise reduction techniques such as wavelet transform, Neural Network, PCA, ICA and mean and median filters over medical images has been discussed. In this paper we tried to highlight the strength and weakness of various noise removal techniques over processing of the medical images.

关键词： Medical diagnostic imaging image edge detection Artificial neural networks Noise reduction Uncertainty Principal component analysis

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A Refined Automatic Co-Registration Method For High-Resolution Optical and Sar images by Maximizing Mutual Information

A Refined Automatic Co-Registration Method For High-Resoluti...

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2016 IEEE International conference on signal and image processing

作者： Faycal Saidi Jie Chen Pengbo Wang School of Electronics and Information Engineering Beihang University

The use of multisensors images for different applications, like change detection and image fusion, require an image to image ***, the image registration becomes a crucial task with the continuous increase in image resolution, especially in urban *** this paper, a refined automatic Mutual Information based registration approach of spaceborne Synthetic Aperture radar(SAR) and optical image is *** data set include Terra Sar-X(1m) and Worldview-2(0.5m) images and cover urban area of San *** approach is divided into two ***, we use Discrete Canny edge detector to extract contours from the optical image, and Gabor-wavelet filter to extract edge from the SAR ***, a rigid transformation(rotation and translation) is applied to the contours image obtained by Canny ***, for each value of transformation, the Mutual Information is computed between this transformed image and the feature image outcome of application of Gaborwavelet to the SAR *** best transformation parameters are obtained when the Mutual Information is ***, in this work, we compared the proposed approach with the basic Mutual Information intensity based registration *** results obtained demonstrated that our approach improve the registration accuracy comparatively to the basic Mutual Information intensity based registration method.

关键词： image registration mutual information gabor-wavelet SAR image canny edge detector

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Identification of Acrylamide in Fried Potato Crisps Using image processing in wavelet Domain 38

Identification of Acrylamide in Fried Potato Crisps Using Im...

引用

38th International conference on Telecommunications and signal processing (TSP)

作者： Singh, Anushikha Dutta, Malay Kishore Burget, Radim Masek, Jan Amity Univ Sect 125 Noida Uttar Pradesh India Brno Univ Technol Fac Elect Engn CS-61090 Brno Czech Republic

ISBN: (纸本)9781479984985

Acrylamide is a toxic carcinogenic material that commonly occurs in heated starchy food items like potato crisps. Identification of such toxic chemical in food items using conventional chemical laboratory based methods is time consuming and expensive and may need specialized manpower for such laboratory testing. This paper proposes an efficient image processing based non-destructive testing method for identification of acrylamide in potato crisps. The image of the potato crisps is automatically segmented and features are extracted from the images in wavelet domain. These features are then analyzed for identification of the presence of acrylamide in these samples. The variation in the various features of the image is related to the presence of acrylamide. The experimental results indicate that the proposed method is efficient for identification of acrylamide from the wavelet features of the images. The proposed method achieves 90% of accuracy and it can be used for real time applications.

关键词： Toxic substances Acrylamide image processing Feature Extraction Discrete wavelet Transform

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Robust Grayscale Watermarking Technique Based on Face Detection 23

Robust Grayscale Watermarking Technique Based on Face Detect...

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23nd signal processing and Communications applications conference (SIU)

作者： Laur, Lauri Daneshmand, Morteza Agoyi, Mary Anbarjafari, Gholamreza Univ Tartu Inst Comp Sci Liivi 2 EE-50409 Tartu Estonia Univ Tartu Inst Technol iCV Grp IMS Lab EE-50411 Tartu Estonia Cyprus Int Univ Fac Engn Lefkosa KKTC Turkey

ISBN: (纸本)9781467373869

Due to increase of usage of digital media distributed over the Internet, concerns about security and piracy have emerged. The amount of digital media reproduction has brought a need for content watermarking. In this paper robust grayscale watermarking technique based on face detection is proposed. Face detection algorithm is used to find a face on host image and this part of image is transformed into frequency domain using Discrete wavelet Transform. Chirp z-transform is applied on low-frequency subband from previous step and LU decomposition is used on the outcome. Diagonal matrix from LU decomposition is further decomposed using Singular Value Decomposition and watermark is embedded into singular values. Numerous experiments are run on that algorithm and results are compared with novel and state-of-the-art techniques. The results show that proposed method has good imperceptibility and robustness characteristics.

关键词： Chirp Z Transform Discrete wavelet Transform face detection LU decomposition Singular Value Decomposition watermarking

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A Novel Approach for the Detection of Diabetic Retinopathy Disease 23

A Novel Approach for the Detection of Diabetic Retinopathy D...

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23nd signal processing and Communications applications conference (SIU)

作者： Alver, Seyfullah Ay, Sinan Tetik, Yusuf Engin Kara Harp Okulu Bilgisayar Muhendisligi Bolumu Ankara Turkey

ISBN: (纸本)9781467373869

Diabetic retinopathy is the most common cause of blindness of the eye depend on diabetes. In this work, a novel approach is presented for the detection of diabetic retinopathy diseases from the retina images. For this purpose, firstly regions which are probably diseased are found and features are extracted from these regions by applying Discrete wavelet Transform. Afterwards the number of found features is reduced by Principal Component Analysis and Naive Bayes is used for the classification of them. This approach differs from the similar works by the way Region of Interest is found and the automatic selection of features instead of using hand-picked ones. It has been shown that the proposed system achieves an accuracy rate up to the 95% in the detection of the diseased retinas.

关键词： Detection of Diabetic Retinopathy Medical image Classification Region of Interest Discrete wavelet Transform Haar Features Principal Component Analysis Naive Bayes Classifier

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Iris image Compression using wavelets Transform Coding 2

Iris Image Compression using Wavelets Transform Coding

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2nd International conference on signal processing and Integrated Networks (SPIN)

作者： Paul, Arnob Khan, Tanvir Zaman Podder, Prajoy Ahmed, Rafi Rahman, M. Muktadir Khan, Mamdudul Haque IEM Dept ECE Kolkata India KUET Dept ECE Khulna 9203 Bangladesh

ISBN: (纸本)9781479959914

Iris recognition system for identity authentication and verification is one of the most precise and accepted biometrics in the world. Portable iris system mostly used in law enforcement applications, has been increasing more rapidly. The portable device, however, requires a narrow-bandwidth communication channel to transmit iris code or iris image. Though a full resolution of iris image is preferred for accurate recognition of individual, to minimize time in a narrow-bandwidth channel for emergency identification, image compression should be used to minimize the size of image. This paper has investigated the effects of compression particularly for iris image based on wavelet transformed image, using Spatial-orientation tree wavelet (STW), Embedded Zero tree wavelet (EZW) and Set Partitioning in hierarchical trees (SPIHT), to identify the most suitable image compression. In this paper, Haar wavelet transform is utilized for image compression and image decomposition, by varying the decomposition level. The results have been examined in terms of Peak signal to noise ratio (PSNR), Mean square Error (MSE), Bit per Pixel Ratio (BPP) and Compression ratio (CR). It has been evidently found that wavelet transform is more effective in the image compression, as recognition performance is minimally affected and the use of Haar transform is ideally suited. CASIA, MMU iris database have been used for this purpose.

关键词： iris recognition image compression mean square error peak signal to noise ratio(PSNR) wavelet decomposition

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Saliency guided wavelet compression for low-bitrate image and Video coding

Saliency guided Wavelet compression for low-bitrate Image an...

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3rd IEEE Global conference on signal and Information processing (GlobalSIP)

作者： Barua, Souptik Mitra, Kaushik Veeraraghavan, Ashok Rice Univ Houston TX 77251 USA Indian Inst Technol Madras Madras Tamil Nadu India

ISBN: (纸本)9781479975914

We propose an improved saliency guided wavelet compression scheme for low-bitrate image/video coding applications. Important regions (faces in security camera feeds, vehicles in traffic surveillance) get degraded significantly at low bitrates by existing compression standards, such as JPEG/JPEG-2000/MPEG-4, since these do not explicitly utilize any knowledge of which regions are salient. We design a compression algorithm which, given an image/video and a saliency value for each pixel, computes a corresponding saliency value in the wavelet transform domain. Our algorithm ensures wavelet coefficients representing salient regions have a high saliency value. The coefficients are transmitted in decreasing order of their saliency. This allows important regions in the image/video to have high fidelity even at very low bitrates. Further, our compression scheme can handle several salient regions with different relative importance. We compare the performance of our method with the JPEG/JPEG-2000 image standards and the MPEG-4 video standard through two experiments: face detection and vehicle tracking. We show improved detection rates and quality of reconstructed images/videos using our Saliency Based Compression (SBC) algorithm.

关键词： Saliency wavelet transform image coding Video coding

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Multiple scaling factors based Semi-Blind watermarking of grayscale images using OS-ELM neural network

Multiple scaling factors based Semi-Blind watermarking of gr...

引用

IEEE International conference on signal processing, Communications and Computing (ICSPCC)

作者： Ankit Rajpal Anurag Mishra Rajni Bala Department of Computer Science University of Delhi New Delhi India

ISBN: (纸本)9781509027095

In this paper, a multiple scaling factor based Semi-Blind watermarking scheme for grayscale image watermarking using Online Sequential Extreme Learning Machine (OS-ELM) is proposed. Four-level DWT is applied on three standard test images of size 512 × 512. LL4 sub-band coefficients are chosen for watermark embedding. OS-ELM is initially tuned with a fixed number of training data used in its initial phase and size of data block learned in each iteration. The training set is developed by combining the quantized and desired LL4 sub-band coefficients. This training set is fed to OS-ELM for training. The output of OS-ELM is a sequence of predicted coefficients which is sorted and divided into three equal parts. Multiple Scaling Factor (MSF) scheme is used for embedding a binary watermark in a Semi-Blind manner. Results show good visual quality of signed images and good similarity between the extracted and original watermarks from signed and attacked images. The PSNR and BER are found to be well optimized both in case of signed and attacked images. The time for embedding and extraction is in milliseconds, which makes the proposed technique effective for developing real time watermarking applications.

关键词： Watermarking Mathematical model Training data Training Gray-scale Visualization Discrete wavelet transforms

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Classification of Breast Masses in Mammogram images using KNN 23

Classification of Breast Masses in Mammogram Images using KN...

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23nd signal processing and Communications applications conference (SIU)

作者： Alpaslan, Nuh Kara, Asuman Zencir, Busra Hanbay, Davut Inonu Univ Bilgisayar Muhendisligi Bolumu Malatya Turkey

ISBN: (纸本)9781467373869

Breast cancer is one of the most deadly diseases for women. Mammogram is very important imaging tecnique used diagnosis in early stages of breast cancer. In this study, a decision support system which helps experts to examine mammogram images in the fight against breast cancer is developed. In this study, firstly several preprocesses are applied to mammogram to make image clear and segmentation of mass is provided with an appropriate threshold value. After the segmentation processes, features of the tumor mass are obtained. The obtained features are classified as normal, benign or malignant using kNN (k-nearest neighbours) classifiers. In this study, its have been were shown that, effect of kurtosis, skewness and wavelet energy features on classification performance is shown. As a result, it has been seen that, these features improve the classification performance.

关键词： Digital Mammography Breast Lump Breast Cancer wavelet energy decision support systems Imaging breast cancer stage images segmentation Cancer fight

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image Compressive Sensing Based on Blended Basis Functions 3rd

Image Compressive Sensing Based on Blended Basis Functions

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3rd International conference on Communications, signal processing, and Systems (CSPS)

作者： Tong, Ying Liu, Leilei Zhao, Meirong Wei, Zilong Tianjin Normal Univ Coll Elect & Commun Engn Tianjin Peoples R China Tianjin Univ State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China

ISBN: (纸本)9783319089911;9783319089904

Compressive sensing (CS) has given us a new idea at data acquisition and signal processing. It has proposed some novel solutions in many practical applications. Focusing on the image compressive sensing problem, the paper proposes an algorithm of compressive image sensing based on the multi-resolution analysis. We present the method to decompose the images by nonsubsampled contourlet transform (NSCT) and wavelet transform successively. It means that the images can be sparse represented by more than one basis functions. We named this process as blended basis functions representation. Since the NSCT and wavelet basis functions have complementary advantages in the image multi-resolution analysis, and the signals are more sparse after decomposed by two kinds of basis functions, the proposed algorithm has perceived advantages in comparison with compressive sensing in the wavelet domain which is widely reported by literatures. The simulations show that our method provides promising results.

关键词： Blended basis functions Compressive sensing NSCT wavelet transform

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