Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Manjunatha, M. B.
- A Robust Technique to Retrieve a Histopathological Images using GLCM Method
Abstract Views :228 |
PDF Views:0
Authors
Affiliations
1 Computer Science Engineering, Jain University, Bangalore - 560069, Karnataka, IN
2 Akshaya Institute of Technology, Tumkur - 572106, Karnataka, IN
1 Computer Science Engineering, Jain University, Bangalore - 560069, Karnataka, IN
2 Akshaya Institute of Technology, Tumkur - 572106, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 10, No 1 (2017), Pagination:Abstract
Image retrieval is like a system of in which, we can do searching and browsing then, finally retrieving a medical image from a very huge given a database of medical images. To identify or examine the image content, there must be some desired approaches. Hence, the goal of the proposed project is to retrieval of the histopathologicl image using CBIR method using GLCM technique. Finally, the results will be calculated by analyzing the results obtained in this method. Then we will calculate the GLCM contrast as well as GLCM correlation to retrieval of an image. These sets will enable new research opportunities, and they will improve and flow benchmark reviews. Our experimental result shows that our novel proposed method achieves better performance.Keywords
GLCM Constrast, GLCM Correlation, Histopathological Image, Image Retrieval, Method, Medical Image- A Hybrid Gesture Recognition Method for American Sign Language
Abstract Views :257 |
PDF Views:0
Authors
Affiliations
1 Electronics Engineering, Jain University, Bangalore - 560069, Karnataka, IN
2 Akshaya Institute of Technology, Tumkur - 572106, Karnataka, IN
1 Electronics Engineering, Jain University, Bangalore - 560069, Karnataka, IN
2 Akshaya Institute of Technology, Tumkur - 572106, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 10, No 1 (2017), Pagination:Abstract
Gesture based communication is a method of correspondence between the ordinary and hard of hearing people in which the vision based procedure is utilized. This paper proposes a novel methodology of hand gesture recognition system for American Sign Language (ASL), which will perceive communication via gestures signals in an ongoing situation. A hybrid based descriptor, which joins the benefits of LBP (Local binary pattern), SP (super pixels) and SURF (Speeded Up Robust Features) strategies, is utilized as a consolidated list of capabilities to accomplish a improved identification rate beside among a little moment in time computational difficulty. In additional increase the detection speed and create the appreciation framework strong to view-point varieties, the idea of derived features from the accessible list of capabilities is presented. K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are utilized for hybrid arrangement of single marked letter. Comparative investigation of these strategies with other well known methods demonstrates that the constant proficiency and robustness are better. The performances parameters will be used in this method are accuracy, sensitivity, precision, FNR and FDR.Keywords
American Sign Language, FNR, FDR, Hand Gesture Recognition, KNN, LBP, Recognition Rate, SP, SURF, SVM- Backend Tools for Speech Synthesis in Speech Processing
Abstract Views :150 |
PDF Views:0
Authors
Affiliations
1 Electronics Engineering, Jain University, Bengaluru - 560069, Karnataka, IN
2 Department of ECE, K.E.C, Kuppam - 517425, Andhra Pradesh, IN
3 A.I.T., Tumkur - 572106, Karnataka, IN
1 Electronics Engineering, Jain University, Bengaluru - 560069, Karnataka, IN
2 Department of ECE, K.E.C, Kuppam - 517425, Andhra Pradesh, IN
3 A.I.T., Tumkur - 572106, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 10, No 1 (2017), Pagination:Abstract
Speech synthesis is an artificial method of converting written text into machine generated speech. The Main Theme of this paper is to describe an overview of existing popular and advanced speech synthesizing techniques. Speech synthesis is a method of artificially generating the human speech from mathematical models and machines using some control parameters. The device which synthesizes is called as a synthesizer, the device which synthesizes is called as synthesizer and the synthesizer may be implemented as hardware or software. So for the research is not successful in generating a speech signal, usually researchers extract the speech parameters from the recorded speech and synthesize the original signal from it. A synthesizer can be viewed as Mathematical modeling of the vocal tract by extracting the acoustic/vocal features to produce the artificial generated speech output. The generated speech quality is described by its naturalness and intelligibility. The naturalness of synthesized speech gives an idea about how closely the generated output resembles the sounds produced by human speech production. Intelligibility describes how about the output can be understood by the listener after the perceiving it.Keywords
HMM, Modelling, Speech Synthesis, TTS, Vocal Tract- Speech Features Extraction Techniques for Robust Emotional Speech Analysis/Recognition
Abstract Views :181 |
PDF Views:0
Authors
Affiliations
1 Electronics Engineering, Jain University, Bangalore – 560069, Karnataka,, IN
2 Department of ECE, KEC, Kuppam – 517425, Andhra Pradesh,, IN
3 A.I.T. Tumkuru – 572106, Karnataka,, IN
1 Electronics Engineering, Jain University, Bangalore – 560069, Karnataka,, IN
2 Department of ECE, KEC, Kuppam – 517425, Andhra Pradesh,, IN
3 A.I.T. Tumkuru – 572106, Karnataka,, IN
Source
Indian Journal of Science and Technology, Vol 10, No 3 (2017), Pagination:Abstract
Speech is the most natural and convenient way of human communication. The speech represents not only a sequence of steady states of some sounds which are abruptly changing from one to another or a sound signal which can be ignored after perceiving or hearing it. But human Speech is a unique signal which carries and conveys multiple levels of knowledge source, linguistic and non-linguistic information. Speech signals are the information bearing signals which are evolved as functions of a single independent variable like time. Speech is a complex acoustic wave resulted as output of speaker’s effort. Speech serves to communicate from speaker to one or more listeners. The typical sound is called phone and it is produced when a phoneme is articulated. Most of Indian languages have 20-50 phonemes which constitute an alphabet of sounds to describe the different words in that language. Generally the speech is composed of sentences made of words. Usually words are composed of phoneme sequences called syllables. Speech analysis plays a vital role in speech recognition and synthesis. Speech analysis is also known as feature extraction or as speech signal front ends.Keywords
Feature Extraction, Front Ends, Human Communication, Speech- An Efficient Chest X-Ray Image Retrieval using CBIR Technique
Abstract Views :248 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, Jain University, Bangalore - 560069, Karnataka, IN
2 Department of ECE, AIT, Tumkur - 572106, Karnataka, IN
1 Department of CSE, Jain University, Bangalore - 560069, Karnataka, IN
2 Department of ECE, AIT, Tumkur - 572106, Karnataka, IN
Source
Indian Journal of Science and Technology, Vol 10, No 4 (2017), Pagination:Abstract
Image feature extraction as well as retrieval of a medical image is a major problems CBIR technique. there is an improvement of networking and communication systems and other tools, which leads to imagine a numerous application for common users. The medical image retrieval is fast growing techniques in all the research fields. Many medical image retrieval approaches are still incapable to provide precise retrieval results along with high visual perception and also very less computational density. To report these issues, this paper illustrates and established a novel methodology for CBIR using 2D-Wavelet Transform (DWT). Here, we going to create a database of medical images utilizing CBIR method. DWT algorithm is applied to extract the feature of given query input image. By getting the horizontal and vertical projections of summation of pixels analyzing of BC coefficients are done. The Bhattacharyya Coefficients (BC) is used to find the similarity score of all the images. Based on the similarity score, the algorithm will select the most suitable images, similar to given query image. The highest value of BC images is the retrieved by the un trained database present in the system.Keywords
Bhattacharyya Coefficients, CBIR Method, Chest X-ray Image, DWT, Healthcare Systems- Analysis of Vocal Tract Shape Variability based on Formant Frequency Ratio at Various Conditions of Vowels for Indian English Speakers
Abstract Views :134 |
PDF Views:0
Authors
Affiliations
1 Electronics Engineering, Jain University, Bangalore – 560069, Karnataka, IN
2 Akshaya Institute of Technology, Tumkur – 572106, Karnataka, IN
1 Electronics Engineering, Jain University, Bangalore – 560069, Karnataka, IN
2 Akshaya Institute of Technology, Tumkur – 572106, Karnataka, IN