2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)最新文献_第9页

Improved fuzzy space-intervals based sequential pattern mining: Technical solution 改进的基于模糊空间间隔的序列模式挖掘:技术解决方案

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435671

Harsha Nair, E. A. Neeba

{"title":"Improved fuzzy space-intervals based sequential pattern mining: Technical solution","authors":"Harsha Nair, E. A. Neeba","doi":"10.1109/ICCIC.2015.7435671","DOIUrl":"https://doi.org/10.1109/ICCIC.2015.7435671","url":null,"abstract":"One of the sub areas of the data mining includes sequential pattern mining. This mining algorithm is to find the repeating patterns after mining the sequence databases. These are used to find the relation between the various items in the data for different purposes. As these data keep changing according to the change in time, mining should be done on incremented or updated database to obtain the frequent sequential patterns. The proposed algorithm in this paper uses modified algorithm of sequential pattern mining including concepts of fuzzy space intervals. In this algorithm, frequently occurring sequential patterns in the sequence database are mined using apriori like method. Fuzzy theory is used for mining the space interval between the frequently occurring sequences. The sequentially occurring candidate patterns are found first. After that follows the frequently occurring sequential patterns, which are found by calculating the minimum fuzzy support along with the use of the fuzzy number. Each space cluster is found by fuzzy support computation. The final results comprises the frequently occurring fuzzy space sequentially based patterns. At last the outcome also confirms the excellence of the suggested MISPFSI algorithm.","PeriodicalId":276894,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129928415","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

Cryptography using inverse substitution & key rotation with seed propagation 使用逆代换的密码术&带种子传播的密钥旋转

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435730

R. K. Pathak, S. Meena

引用次数: 1

A novel semi-blind video watermarking using KAZE-PCA-2D Haar DWT scheme 一种基于KAZE-PCA-2D Haar DWT的半盲视频水印算法

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435721

K. L. Prasad, T. C. M. Rao, V. Kannan

{"title":"A novel semi-blind video watermarking using KAZE-PCA-2D Haar DWT scheme","authors":"K. L. Prasad, T. C. M. Rao, V. Kannan","doi":"10.1109/ICCIC.2015.7435721","DOIUrl":"https://doi.org/10.1109/ICCIC.2015.7435721","url":null,"abstract":"In this research article the digital video watermarking technique is projected through a semi-blind pattern. The proposed method involves frame-spot matching model based on KAZE method at the initial stage, The KAZE method is deployed for matching the edge points of frame-spots with all video frames with the intention to detect the embedding and extract the respective regions. Then the frame entropy blocks are designated and converted by PCA (Principal Component Analysis) blocks. The QIM (Quantization Index Modulation) is employed to quantize the highest coefficient values on each PCA entropy chunks of every sub-band. The single shared secure key is employed to recover the watermarked content. The DWT (Discrete Wavelet Transform) is applied on every single video frame and disintegrate into group of sub-bands. During extraction this is simply reversed; however the KAZE frame-spot is harmonized through each frame edge points. The parameters like rotation, scaling and translation are assessed and the watermarked evidence can be effectively extracted. The proposed pattern is verified using a numerous of video structures and compared with other similar models such as SURF, SIFT, PCA-SIFT, KAZE and perceived high optimal results. The investigational outcomes demonstrated high imperceptibility and high strength against numerous outbreaks like JPEG encoding, addition of Gaussian noise, gamma modification, histogram equality and contrast rectification in both forms of ordinary videos and clinical videos.","PeriodicalId":276894,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127709350","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: 3

Machine learning approach for exploring rock arts through the cloud infrastructure 通过云基础设施探索岩石艺术的机器学习方法

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435682

R. S. Ponmagal, N. Srinivasan

{"title":"Machine learning approach for exploring rock arts through the cloud infrastructure","authors":"R. S. Ponmagal, N. Srinivasan","doi":"10.1109/ICCIC.2015.7435682","DOIUrl":"https://doi.org/10.1109/ICCIC.2015.7435682","url":null,"abstract":"This paper is aimed at proposing a machine learning approach to analyze and make sense out of the ancient rock arts by exploring them through cloud infrastructure. The visual language of the rock art is proposed to be interpreted and transformed into the current language of human cognition. The rock arts can be captured as 3D motion pictures; ultrasonically detected images; pictures captured using laser sensors and thermography techniques. Since the countries across the Globe are rich in culture and also diverse in nature, rock arts have been explored and keeping on exploring more in quantity, the rock arts information collected through the above said methods can be represented and processed using cloud infrastructure. Further, using machine learning algorithms in the cloud is proposed, to arrive at definite, meaningful information from rock arts. Through the machine learning approach, the symbols represented by rock arts could be matched with the twenty six English alphabets. The proposed work is the interpretation of the olden rock art scripts and hence to predict the meaning that they wish to convey.","PeriodicalId":276894,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127639726","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

An improved image retrieval system using optimized FCM & multiple shape, texture features 一个改进的图像检索系统，使用优化的FCM和多种形状，纹理特征

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435666

N. Neelima, E. Reddy

引用次数: 3

Shadow detection and removal by object-wise segmentation 基于对象分割的阴影检测和去除

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435784

K. Divya, K. Roshna, Shelmy Mathai

引用次数: 3

Feature selection using Binary-ABC algorithm for DWT-based face recognition 基于二进制abc算法的人脸识别特征选择

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435632

Malepati Bala Siva Sai Akhil, P. Aashish, K. Manikantan

引用次数: 2

Markov chain based stochastic model of electric vehicle parking lot occupancy in vehicle-to-grid 基于马尔科夫链的车对网电动汽车停车场占用随机模型

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435806

Santosh Kumar, R. Udaykumar

引用次数: 6

Automatic 2D to 3D video and image conversion based on global depth map 基于全局深度图的自动2D到3D视频和图像转换

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435781

Shelmy Mathai, Paul P. Mathai, K. Divya

{"title":"Automatic 2D to 3D video and image conversion based on global depth map","authors":"Shelmy Mathai, Paul P. Mathai, K. Divya","doi":"10.1109/ICCIC.2015.7435781","DOIUrl":"https://doi.org/10.1109/ICCIC.2015.7435781","url":null,"abstract":"3d technology brings a new era of entertainment to the human race. It offered a wide array of possibilities in near future in almost every walk of life and in entertainment segment. 3D content generation is the important step in 3D systems. Special cameras such as stereoscopic dual camera, depth range camera etc. are designed to generate the 3D model of a scene directly. There are different techniques to generate the 3D content. But the problem is our current and past media data are in 2D which needs to convert into 3D. This is where the importance of 2D to 3D transformation arises. In this paper proposed real time 3D image and video creation by depth map estimation. Depth map estimation can be done in two methods. One is based on depth fusion method and other is based on saliency map of an image. In dataset image estimate the depth map from depth fusion method and then depth is refined by color spatial variance. In non dataset images we find depth map by global saliency method. Experimental result demonstrates that the proposed technique convey better performance compared to the state-of-the-art of methods.","PeriodicalId":276894,"journal":{"name":"2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130389906","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: 8

Image segmentation using snake model with nosie adaptive fuzzy switching median filter and MSRM method 基于自适应模糊切换中值滤波和MSRM方法的蛇形模型图像分割

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) Pub Date : 2015-12-01 DOI: 10.1109/ICCIC.2015.7435798

Sajal Pahariya, S. Tiwari

引用次数: 1