ICTACT Journal on Image and Video Processing最新文献_第2页

BRAIN TUMOUR SEGMENTATION STRATEGIES UTILIZING MEAN SHIFT CLUSTERING AND CONTENT BASED ACTIVE CONTOUR SEGMENTATION 利用均值移位聚类和基于内容的活动轮廓分割的脑肿瘤分割策略

ICTACT Journal on Image and Video Processing Pub Date : 2019-05-01 DOI: 10.21917/ijivp.2019.0284

D. Mahalakshmi, S. Sumathi

{"title":"BRAIN TUMOUR SEGMENTATION STRATEGIES UTILIZING MEAN SHIFT CLUSTERING AND CONTENT BASED ACTIVE CONTOUR SEGMENTATION","authors":"D. Mahalakshmi, S. Sumathi","doi":"10.21917/ijivp.2019.0284","DOIUrl":"https://doi.org/10.21917/ijivp.2019.0284","url":null,"abstract":"This paper proposes an automatic brain tumor segmentation using Mean shift clustering and content based active contour segmentation. In diagnosis of the disease medical imaging has more advantages. Many people suffer from brain tumor, it is a serious and dangerous disease. A brain tumor occurs when abnormal cells form in the brain. A proper diagnosis of brain tumor is provided by the medical imaging. The detection of tumor from brain is an important and difficult task in the medical field. One essential part in detecting the tumor is image segmentation. The brain tumor detection technique in the MRI images is very significant in many symptomatic and cure applications. In view of high amount information in MRI pictures, tumor segmentation and classification are hard. The image segmentation is performed on different dataset of MRI cerebrum tumor pictures. The segmentation gives an automatic brain tumor recognition method to build the exactness, yields with decline in the analysis time. The image segmentation technique includes image acquisition, image preprocessing, denoising, and finally the feature extraction. The input image is pre-processed using wiener filtering and the noise is removed using Edge Adaptive Total Variation Denoising (EATVD) technique. Once the noise is removed from the image, it undergoes segmentation process, where Mean Shift Clustering and Content based active segmentation techniques are used. Finally, the features are extracted from the segmented image using gray level co-occurrence matrix (GLCM). The image segmentation is implemented using MATLAB software. Finally, the tumor is segmented and energy, contrast, correlation, homogeneity is extracted, and comparison results are","PeriodicalId":30615,"journal":{"name":"ICTACT Journal on Image and Video Processing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42676313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

AN EFFICIENT AND EFFECTIVE TECHNIQUE FOR MARKER DETECTION AND POSE ESTIMATION USING A MONOCULAR CALIBRATED CAMERA 利用单目标定相机进行标记检测和姿态估计的高效技术

ICTACT Journal on Image and Video Processing Pub Date : 2019-05-01 DOI: 10.21917/ijivp.2019.0281

J. Jayakumari, S. Anand, M. Madan, R. Misha

{"title":"AN EFFICIENT AND EFFECTIVE TECHNIQUE FOR MARKER DETECTION AND POSE ESTIMATION USING A MONOCULAR CALIBRATED CAMERA","authors":"J. Jayakumari, S. Anand, M. Madan, R. Misha","doi":"10.21917/ijivp.2019.0281","DOIUrl":"https://doi.org/10.21917/ijivp.2019.0281","url":null,"abstract":"The basic idea of all image processing methods is to process images captures by the camera device. Using image processing techniques, it is possible to find and process markers, faces, natural objects, simple shapes and other objects. One of the techniques is based on the use of markers, both artificial and natural. Markers on image are used for determining objects around or about the current location of the user. This method is also known as marker-based tracking. Markers in this method can provide a reference coordinate system for producing graphical overlays over the real components on the images. Marker identification is an important part of marker-based tracking process. A good marker is considered to be a marker that can be easily and reliably detected under different circumstances. The process of marker detection consists of two stages: Image pre-processing and Identification of potential markers. Marker processing algorithm and steps related to image processing and detection of potential marker stages are: Acquisition of a source image, Image pre-processing and Detection of potential markers. This paper discusses a simple marker detection algorithm and its simulation in MATLAB for verification. A potential application of marker detection to estimate the pose of the marker in real time is also implemented and the results are discussed.","PeriodicalId":30615,"journal":{"name":"ICTACT Journal on Image and Video Processing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47815672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PERFORMANCE-BASED STUDY ON DIAMOND SEARCH AND ITS VARIATIONS FOR EFFICIENT MOTION ESTIMATION IN VIDEO 基于性能的菱形搜索及其变体在视频中高效运动估计中的研究

ICTACT Journal on Image and Video Processing Pub Date : 2019-05-01 DOI: 10.21917/ijivp.2019.0283

Hussain Ahmed Choudhury, N. Sinha, T. H. Sardar, Archana Wagh-Mare

引用次数: 0

CARDIOVASCULAR SIGNAL RATE DETECTION USING FREQUENCY DOMAIN TRANSFORM 基于频域变换的心血管信号速率检测

ICTACT Journal on Image and Video Processing Pub Date : 2019-05-01 DOI: 10.21917/ijivp.2019.0285

J. Mary, C. Rekha

引用次数: 0

AUTOMATED HUMAN DETECTION AND TRACKING FOR SURVEILLANCE APPLICATIONS 用于监视应用的自动人体检测和跟踪

ICTACT Journal on Image and Video Processing Pub Date : 2019-03-06 DOI: 10.21917/ijivp.2019.0280

Amritha Sharma, Milind Pathak, Avaneesh Tripathi, P. Vijay, S. Jain

引用次数: 1

PRIVACY PRESERVATION OF VIDEOS USING NEUTROSOPHIC LOGIC BASED SELECTIVE ENCRYPTION 基于中性粒细胞逻辑的选择性加密在视频隐私保护中的应用

ICTACT Journal on Image and Video Processing Pub Date : 2019-02-01 DOI: 10.21917/ijivp.2019.0278

Sayyada Fahmeeda Sultana, D. Shubhangi

{"title":"PRIVACY PRESERVATION OF VIDEOS USING NEUTROSOPHIC LOGIC BASED SELECTIVE ENCRYPTION","authors":"Sayyada Fahmeeda Sultana, D. Shubhangi","doi":"10.21917/ijivp.2019.0278","DOIUrl":"https://doi.org/10.21917/ijivp.2019.0278","url":null,"abstract":"Having great photos and video phone, but what happens when you decide to buy a new phone or your storage becomes too full to take any more, back it all on the cloud. It’s no secret that videos are a valuable way of communicating information. With attention spans dropping and the need to get larger amounts of information across in a shorter period of time, a well-placed video can take your presentation to the next level these presentations need to be up to date and available wherever you are, back it all on the cloud. Better collaboration and communication through the use of cloud as cloud allows users to access the latest versions of any multimedia data (text, video, images, audio, etc), so they can stay on top changes, which can help businesses to better manage their work flow, regardless of geographical location or spread. Multimedia data like videos stored on cloud are vulnerable to various types of threats like known plain text attach, threat to data, denial of service, etc. To overcome these problems videos need to be encrypted before it gets stored on cloud. Encrypting whole video is a time consuming task, to get rid of time complexity videos can be encrypted using selective encryption many researchers in the state of art have proposed techniques for selective image encryption. In this paper, a frame work is proposed for selective encryption of videos in two stages. The first stage is, Region of interest (ROI) identification performed based on Neutrosophic Logic, watershed image segmentation method. Second Stage is ROI encryption which is performed using the proposed Decision Based Encryption (DBE) Algorithm. The proposed frame work is fast, robust, highly scalable and accurate to meet the need of current internet bandwidth and speed.","PeriodicalId":30615,"journal":{"name":"ICTACT Journal on Image and Video Processing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49660225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

SURVEY OF SUPER RESOLUTION TECHNIQUES 超分辨率技术综述

ICTACT Journal on Image and Video Processing Pub Date : 2019-02-01 DOI: 10.21917/ijivp.2019.0273

Anand Deshpande, P. Patavardhan

引用次数: 5

COMPUTATIONAL MODEL FOR CREATING NEURAL NETWORK DATASET OF EXTRACTED FEATURES FROM IMAGES CAPTURED BY MULTIMEDIA SECURITY DEVICES 用于创建从多媒体安全设备捕获的图像中提取特征的神经网络数据集的计算模型

ICTACT Journal on Image and Video Processing Pub Date : 2019-02-01 DOI: 10.21917/ijivp.2019.0276

E. J. Garba, Darious Tienhua Chinyio

引用次数: 2

HIDE IMAGE AND TEXT USING LSB, DWT AND RSA BASED ON IMAGE STEGANOGRAPHY 基于图像隐写技术，使用lsb, DWT和rsa隐藏图像和文本

ICTACT Journal on Image and Video Processing Pub Date : 2019-02-01 DOI: 10.21917/ijivp.2019.0275

Swati Bhargava, M. Mukhija

{"title":"HIDE IMAGE AND TEXT USING LSB, DWT AND RSA BASED ON IMAGE STEGANOGRAPHY","authors":"Swati Bhargava, M. Mukhija","doi":"10.21917/ijivp.2019.0275","DOIUrl":"https://doi.org/10.21917/ijivp.2019.0275","url":null,"abstract":"In this modern era, where technology is increasing at rapid pace and made all day new developments, security is of highest priority. To protect facts into the unrecognizable form diverse technique are used for records hiding like steganography and cryptography techniques have been advanced. This paper securing the image by way of encryption is completed by LSB bits, DWT and RSA algorithm. This paper additionally presents new strategies wherein cryptography and steganography are mixed to scramble the information and in addition to cover the insights in some other medium through image processing (IP). The encrypted picture can be hiding in some other image by way of the use of LSB bits, DWT strategies so that the secret’s message exists. RSA algorithm applied, receiver will use his/her private key because the secret data have been encrypted by recipient public key. Hide encrypted image in the cover image by DWT. Extract encrypted image from cover image and decrypt text by DWT. The proposed scheme is implemented in MATLAB platform the use of preferred cryptography and steganography set of regulations. Calculate PSNR and MSE. Also calculate the entropy of cover image and stego image. This method is secure for communication in the digital world with the digital data transmission.","PeriodicalId":30615,"journal":{"name":"ICTACT Journal on Image and Video Processing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49075577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

DETECTION AND CLASSIFICATION OF BREAST CANCER USING SUPPORT VECTOR MACHINE AND ARTIFICIAL NEURAL NETWORK USING CONTOURLET TRANSFORM 基于contourlet变换的支持向量机和人工神经网络对乳腺癌的检测与分类

ICTACT Journal on Image and Video Processing Pub Date : 2019-02-01 DOI: 10.21917/ijivp.2019.0279

Soumya Hundekar, Saritha Chakrasali

引用次数: 1