Informatics Publishing Limited

T. Venkat Narayana Rao ¹, A. Govardhan ²

Affiliations
1 C.V.R College of Engg., Jawaharlal Technol. University, Hyderabad, A.P, IN
2 Dept. of Computer Science & Engg., Jawaharlal Technol. University, Hyderabad, IN

Abstract

This paper, discuss the features and concepts pertaining to the three popular visible reversible watermarking algorithms and analyze them to evaluate with metrics such as MSE and PSNR values based on implementation i.e. a) Wavelet based watermarking technique b) Tian's difference expansion technique c) LSB-prediction error expansion technique. It is recommended to adopt new reversible data-embedding technique called Least Significant Bit prediction-error expansion which exploits the correlation inherent in the neighborhood of a pixel and provides an effective method for data embedding than the difference-expansion wavelet based schemes. Reversibility aspect ensures image verification, security , lossless embedding and also extraction of images during the damage of source images itself (i.e., image recovery process).

Keywords

Watermark, Data Embedding, Data Security

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T. Venkat Narayana Rao ¹, A. Govardhan ²

Affiliations
1 JNTUK and SNIST, Hyderabad - 501301, IN
2 SIT, Department of CSE, JNTUH, Hyderabad - 500085, IN

Abstract

Background: Worldwide and across India breast cancer is the most common cause of cancer deaths in women. Early or timely detection leads to decrease in the mortality rate. Hence, classification of patients based on the size of the tumor/abnormal masses and less treatment cost must be high priority. Methods/Statistical Analysis: In this paper mammogram images are being acquired from real time and standard databases for imaging the suspected patients. The main purposes of the suggested methods are to diagnose the cancer using fuzzy rules with minimum phases in implementation. Important factors were drawn from the images for subsequent investigation and analysis with the help of Fuzzy Enhanced Mammogram Segmentation scheme. The paper presents two methods and is implemented in (i.e. FEM1 and FEM2) Mat lab programming environment. Results: The images examined were marked by qualified Radiologist and extracted the images using Photoshop tool. The proposed methodologies were evaluated for real images and Mammographic Image Analysis Society (MIAS) database images consists of 320 images for 160 patients each of 1024x1024 resolutions based gray level images. Based on the results it is found that the CDR for FEM1 is 87% whereas FEM2 demonstrates only 77% and also takes 6.25 times lesser execution time. Radiologists need more precise and reduced processing time making the outcome of FEM1 method more practicable. For the evaluation of performance, statistical properties like Similarity Index (SI), Correct Detection Ratio (CDR), and Under Segmentation Error (USE) are computed. The paper presents computations of segmentation efficiency, enhancement performance and comparative analysis between the method 1 and method 2 in terms of segmentation efficiency and CPU processing time. Finally Support Vector Method is used to classify whether the mammogram under test is normal or abnormal. Conclusion: FEM1 outperforms other similar methods. The proposed work provides faster, accurate results and more useful for the diagnosis and classify the abnormal tumors or masses at a cheaper cost.

Keywords

Enhancement, Fuzzy, Image Classification, Image Segmentation, Mammogram, Wavelet

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T. Venkat Narayana Rao ¹, A. Govardhan ², Syed Jahangir Badashah ³

Affiliations
1 Tirumala Engineering College, Bogaram, Kesara, RR District, A.P., IN
2 Jawaharlal Nehru Technological University, Hyderabad, College of Engineering, Jagityala, A.P., IN
3 Sathyabama University, Chennai, IN

Abstract

This paper proposes a reversible data hiding mechanism based on multiresolution analysis with difference expansion algorithm. Based on the multiresolution analysis of an image, gradient information of crude original image is exploited to select proper embedding areas. Adaptively embedding method based on Difference Expansion Algorithm is proposed to embed data into the host image without causing overflow/underflow and distortion problems. The original host image can be obtained upon the extraction of the embedded information. Driving application of reversible date hiding is authentic and can be used in some special applications, such as law enforcement, banks, medical and military fields, where original cover media is required for legal reason. Embedding data into cover media while keeping the media reversible opens a new door for linking some data with original media. With this proposed method we ensure that the Host information improves the compression efficiency, and thus the lossless data embedding capability is achieved. Experimental results signify that the proposed reversible data hiding method can embed a large payload with low visual distortion in the host image.

Keywords

Reversible, Data Hiding, Authentication, Lossless Extraction, Multi-Resolution, Embedding, Peak Signal to Noise Ratio, Stego-Image.

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T. Venkat Narayana Rao ¹, Jella Shruthi ², Thakkallapally Sneha ²

Affiliations
1 Computer Science and Engineering, Sreenidhi Institute of Science and Technology, IN
2 Computer Science and Engineering, Sreenidhi Institute of Science and Technology, Ghatkesar, T.S., IN

Abstract

Now a days , web injection exhibits in different modes, but basically occurs when malicious and unwanted actors tamper directly with browser sessions for their business profits. Malware's are injected through ad networks into websites. How an individual play different roles in this kind of tampering browsers is being discussed. The consequences of malware attacks are explored, as these are new trends in website attacks and describe types of malware you need to watch out on your site. Finally, this paper discusses solutions for reducing malware threats and also includes some best practices for protecting website and business.

Keywords

Malware, Spyware, Cybercriminals, Spammers, Ransomware.

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Anand Kumar Singh ¹, Umang Kumar Singh ¹, Mahathi Penmetsa ¹, T. Venkat Narayana Rao ²

Affiliations
1 Hyderabad Institute of Technology and Management, R.R Dist, Hyderabad, T.S., IN
2 Department of CSE, SNIST, R.R Dist, Hyderabad , T.S., IN

Abstract

AIDE is an idea in advance that only ensures safe navigation, but also lets you link up to the universe. AIDE projects a transparent image into the driver's field of view which appears to roam out of doors of the windscreen. The icon is centered in the space and then the track remains in focus while the driver looks at the information presented by AIDE. This, combined with touchless gesture control, means that the driver is able to use AIDE without ever holding their eyes off the road. When you synchronize the device with your Android handset or iPhone and by placing the AIDE onto your car's dashboard. With this we can start communicating with the vehicle and other people without ever removing your eyes off the road. It is designed to give relevant information at a glance and the power to respond to that information with voice and theme song-less gesture controls i.e. embedded with IR camera and internal microphone. It grows better as it possess an accelerometer, an e-compass and an ambient brightness sensing element. The device, which is to be designed to run on Android 5.0 has transparent HUD display of 5.1-inch and has Wi-Fi and Bluetooth for connectivity. For the touch less controls, in terms of navigating it employs an IR camera , it also includes a GLOAN-ASS, digital compass, accelerometer and ambient brightness sensor. It can also warn us when car needs to be served next and when oil needs replacement. This paper present a novel and useful interface for the future automated vehicles and disabled people.

Keywords

IR Camera, Transparent Hud Display, Accelerometer, Digital Compass, GLOAN-ASS and Ambient Light Sensing Element.

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M. Ravinder ¹, T. Venu Gopal ², T. Venkat Narayana Rao ³

Affiliations
1 Computer Science and Engineering, Geethanjali College of Engineering & Technology, Cheeryal, R.R.Dist, IN
2 Computer Science and Engineering, JNTUCEH, Jagityal, Karimnagar, IN
3 Hyderabad Institute of Technology & Management (HITAM), R.R.District, IN

Abstract

Video data indexing and retrieval which applies tags to large video databases, is useful as a complementary means for applications which are having multi media content and need faster search responses. Well-ordered and effective management of video documents depends on the availability of indexes. Manual indexing is not viable for large video collections in this modern era of information super highway. There is a want for a techniques and frameworks that can store, handle, search and retrieve the data from the huge media archive. This paper discusses about application areas, emerging challenges of video indexing & retrieval, and some future directions for video indexing, video retrieval management system.

Keywords

Video Indexing, Information Retrieval, Annotations, Semantic Gap, VDBMS.

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T. Venkat Narayana Rao ¹, Sohail Ali Shaik ¹, S. Manminder Kaur ¹

Affiliations
1 Department of Computer Science and Engineering, Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Rangareddy, IN

Abstract

Predictive analytics plays an important role in the decision-making process and intuitive business decisions, by overthrowing the traditional instinct process. Predictive analytics utilizes data-mining techniques in order to predict the future outcomes with a high level of certainty. This advanced branch of data engineering is composed of various analytical and statistical methods which are used to develop models that predict the future occurrences. This paper examines the concepts of predictive analytics and various mining methods to achieve the prior. In conclusion, paper discusses process and issues involved in the knowledge discovery process.

Keywords

BigData, Predictive Analytics, Predictive Modelling, Data Mining, Prediction.

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T. Venkat Narayana Rao ¹, A. Govardhan ², Syed Jahangir Badashah ³

Affiliations
1 Computer Science and Engineering, Hyderabad Institute of Technology and Management, Hyderabad, A P, IN
2 College of Engineering, Jawaharlal Nehru Technological University, Nachupally, Karimnagar, A P, IN
3 Sathyabama University, Chennai, IN

Abstract

Edge detection is the most important feature of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms/operators. Computer vision is rapidly expanding field that depends on the capability to perform faster segments and thus to classify and infer images. Segmentation is central to the successful extraction of image features and their ensuing classification. Powerful segmentation techniques are available; however each technique is ad hoc. In this paper, the computer vision investigates the sub regions of the composite image, brings out commonly used and most important edge detection algorithms/operators with a wide-ranging comparative along with the statistical approach. This paper implements popular algorithms such as Sobel, Roberts, Prewitt, Laplacian of Gaussian and canny. A standard metric is used for evaluating the performance degradation of edge detection algorithms as a function of Peak Signal to Noise Ratio (PSNR) along with the elapsed time for generating the segmented output image. A statistical approach to evaluate the variance among the PSNR and the time elapsed in output image is also incorporated. This paper provides a basis for objectively comparing the performance of different techniques and quantifies relative noise tolerance. Results shown allow selection of the most optimum method for application to image.

Keywords

Edge Detection, Image Processing, PSNR, Anova, Mean Square Error, Sub-Images, Hysteresis, Kernel and Variance.

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