Goyani Mahesh

Veer Narmad South Gujarat University, Computer, Alumnus

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Experienced Assistant Professor with a demonstrated history of working in the higher education industry. Skilled in Photography, Computer Science, C , Lecturing, and Drawing. Strong education professional with a Ph.D. focused in Facial Expression Recognition from CHAROTAR UNIVERSITY OF SCIENCE AND TECHNOLOGY.
Address: Ahmedabad, Gujarat, India

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Comparative Analysis between DCT & DWT Techniques of Image Compression

by Goyani Mahesh and Anil Katharotiya

Journal of Information Engineering and …, 2011

Image compression is a method through which we can reduce the storage space of images, videos whi... more

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Comparative Analysis between DCT & DWT Techniques of Image Compression

by Anil Katharotiya and Goyani Mahesh

Image compression is a method through which we can reduce the storage space of images, videos whi... more Image compression is a method through which we can reduce the storage space of images, videos which will helpful to increase storage and transmission process’s performance. In image compression, we do not only concentrate on reducing size but also concentrate on doing it without losing quality and information of image. In this paper, two image compression techniques are simulated. The first technique is based on Discrete Cosine Transform (DCT) and the second one is based on Discrete Wavelet Transform (DWT). The results of simulation are shown and compared different quality parameters of its by applying on various images

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Euler Number, Symmetry and Histogram Based Hierarchical Approach for English OCR

Recognizing text from scanned document is the classical problem of pattern recognition and image ... more Recognizing text from scanned document is the classical problem of pattern recognition and image processing. In this paper, we have proposed hierarchical algorithm for English Optical Character Recognition (OCR). Beauty of this algorithm is that it does not need any features or classifiers like Neural Network (NN) or Support Vector Machine (SVM). Proposed approach recognizes various characters at different level of its hierarchy using Euler property, symmetry and histogram. We have exploited geometric shape of characters for recognition process.

Performance Enhancement in Lip Synchronization Using MFCC Parameters

Many multimedia applications and entertainment industry products like games, cartoons and film du... more Many multimedia applications and entertainment industry products like games, cartoons and film dubbing require speech driven face animation and audio-video synchronization. Only Automatic Speech Recognitionsystem (ASR) does not give good results in noisy environment. Audio Visual Speech Recognition system plays vital role in such harsh environment as it uses both – audio and visual – information. In this paper, we have proposed a novel approach with enhanced performance over traditional methods that have been reported so far. Our algorithm works on the bases of acoustic and visual parameters to achieve better results. We have tested our system for English language using MFCC and LPC parameters of the speech. Lip parameters like lip width, lip height etc are extracted from the video and these both acoustic and visual parameters are used to train neural network. Our system is giving almost cent percent response against vowels.

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Comparative Analysis between DCT & DWT Techniques of Image Compression

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Comparison of different image retrieval techniques in CBIR

Content based image retrieval (CBIR) considers the characteristics of the image itself, for examp... more Content based image retrieval (CBIR) considers the characteristics of the image itself, for example its shapes, colors and textures. CBIR has many applications areas such as, education, commerce, military, searching, bio medicine and web image classification. The domain of CBIR is expanding day by day, the requirements have become complex and so are the algorithms. CBIR is a new but widely adopted method for finding images from vast and unannotated image databases. In CBIR images are indexed on the basis of low-level features, such as color, texture, and shape that can automatically be derived from the visual content of the images. In this paper we have discussed five different image processing techniques. I. INTRODUCTION Content Based Image Retrieval (CBIR) is a technique which uses visual contents, normally known as features, to search images from large scale image databases according to user's requests in the form of a query image. The commercial CBIR system available up to d...

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Top Down Hierarchical Histogram Based Approach for Printed Devnagri Script Charecter Isolation

Communications in Computer and Information Science, 2011

... Trusha Gajjar 1, Rekha Teraiya 2, Gunvantsinh Gohil 3, and Mahesh Goyani 4 1 Department of Co... more

Chain Code and Holistic Features Based OCR System for Printed Devanagari Script Using ANN and SVM

by International Journal of Artificial Intelligence (IJAIA) and Goyani Mahesh

Optical Character Recognition Systems are getting more and more attention in recent decade. In ma... more Optical Character Recognition Systems are getting more and more attention in recent decade. In many countries, OCR has been a part of their government sectors like post offices, Library automation, License Plate Recognition, Defence organization etc. According to recent survey, there are at least 550 million people are using Devanagari script for communication. Hindi is one of the language, which is derived from Devanagari script. For any character recognition system, essential step is to identify individual character and find features to compare it with the template features. In this paper, we have proposed histogram based
hierarchical approach for isolating individual character from the image document. We have used Principle Component Analysis and Fisher Discriminant Analysis kind of holistic features for recognition. We have done the comparisons of such holistic features with geometric features like binary features and chain code.

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Performance Analysis of Block and Non Block Based Approach of Invisible Image Watermarking Using SVD in DCT Domain

Nowadays image authentication plays a vital role for security. Watermarking techniques facilitate... more Nowadays image authentication plays a vital role for security. Watermarking techniques facilitate to hide the data in carrier image in such a way so that data would become imperceptible. Watermarking can be performed either in spatial domain or in transfer domain. Least Significant Bit (LSB) modification is the simple but non reliable theme, which is performed in spatial domain. In transfer domain, Singular Value Decomposition (SVD), Discrete Cosine Transformation (DCT), Fast Fourier Transformation (FFT), Discrete Wavelet Transformation (DWT) and Fast hadamard Transform (FHT) etc provide robust result. The goal of the paper is to present how such methods are useful to authenticate images and avoid image tampering. In our work, we have discussed block and non block based watermarking scheme performed in DCT domain using SVD. Several experiments are carried out to check the robustness of the algorithm. We conclude that non block based algorithm is superior in terms of visual quality after embedding and extraction, while its inferior in terms of some common signal processing attacks like rotation, scaling, translation etc.

Robust Face Recognition in Low Dimensional Subspace Using Reconstructive and Discriminative Features

... 4. Neeta Nain, Prashant Gour, nitish Agrawal, Rakesh Talwar, Subhash Chandra, “Face Recogniti... more

Geometry and Skin Color Based Hybrid Approach for Face Tracking in Colour Environment

Face detection and face tracking has been a fascinating problem for image processing researchers ... more Face detection and face tracking has been a fascinating problem for image processing researchers during the last decade because of many important applications such as video face recognition at airports and security check-points, digital image archiving, etc. In this paper, we attempt to detect faces in a digital image using skin colour segmentation, morphological processing and acceptance/rejection based on face geometry. Face colour segmentation is done with different colour models like RGB and HSV for better results. The same algorithm is later on used for face tracking. Face tracking and video surveillance are some of the noticeable applications of the face detection. Face tracking in offline video is implemented using Skin Colour Segmentation algorithm. We have tested our system for standard face datasets CVL and LFW for face detection. Offline videos are recorded in current working environment with dynamic conditions. Results talk about the robustness of proposed algorithm.

Key Frame Detection Based Semantic Event Detection and Classification Using Heirarchical Approach for Cricket Sport Video Indexing

In this paper, we propose a key frame detection based approach towards semantic event detection a... more In this paper, we propose a key frame detection based approach towards semantic event detection and classification in cricket videos. The proposed scheme performs a top-down event detection and classification using hierarchical tree. At level 1, we extract key frames for indexing based upon the Hue Histogram difference. At level 2, we detect logo transitions and classify the frames as realtime or replay fragments. At level 3, we classify the realtime frames as field view, pitch view or non field view based on colour features such as soil colour for pitch view and grass colour for field view. At level 4, we detect close up and crowd frames based upon edge detection. At level 5a, we classify the close up frames into player of team A, player of team B and umpire based upon skin colour and corresponding jersey colour. At level 5b, we classify the crowd frames into spectators, player’s gathering of team A or player’s gathering of team B. Our classifiers show excellent results with correct detection and classification with reduced processing time.

Performance Analysis of Lip Synchronization Using LPC, MFCC and PLP Speech Parameters

Many multimedia applications and entertainment industry products like games, cartoons and film du... more Many multimedia applications and entertainment industry products like games, cartoons and film dubbing require speech driven face animation and audio-video synchronization. Only Automatic Speech Recognition system (ASR) does not give good results in noisy environment. Audio Visual Speech Recognition system plays vital role in such harsh environment as it uses both - audio and visual - information. In this paper, we have proposed a novel approach with enhanced performance over traditional methods that have been reported so far. Our algorithm works on the bases of acoustic and visual parameters to achieve better results. We have tested our system for English language using LPC, MFCC and PLP parameters of the speech. Lip parameters like lip width, lip height etc are extracted from the video and these both acoustic and visual parameters are used to train systems like Artificial Neural Network (ANN), Vector Quantization (VQ), Dynamic Time Warping (DTW), Support Vector Machine (SVM). We have employed neural network in our research work with LPC, MFCC and PLP parameters. Results show that our system is giving very good response against tested vowels.

ijma by Goyani Mahesh

WICKET FALL CONCEPT MINING FROM CRICKET VIDEO USING A-PRIORI ALGORITHM

by Goyani Mahesh and The International Journal of Multimedia (IJMA) - ERA Indexed

In this paper, we propose an algorithm to detect semantic concepts from cricket video. In our pre... more In this paper, we propose an algorithm to detect semantic concepts from cricket video. In our previous work, we have proposed key frame detection based approach for semantic event detection and classification. The proposed scheme works in two parts. In first part a top-down event detection and classification is performed using hierarchical tree. In second part, higher level concept is identified by applying A-Priori algorithm. In part 1, key frames are identified based on Hue Histogram difference at level 1. At level 2, logo transitions classify the frames as real-time or replay. At level 3, we classify the real time frames as field view, pitch view or non field view based on thresholds like Dominant Soli Pixel Ration (DSPR) and Dominant Grass Pixel Ration (DGPR). At level 4, we detect close up and crowd frames based upon edge detection. At level 5a, we classify the close up frames into player of team A, player of team B and umpire based upon skin colour and corresponding jersey colour. At level 5b, we classify the crowd frames into spectators, player’s gathering of team A or player’s gathering of team B. In part two, labels are associated with each frame event, which is used as input to A-Priori algorithm for concept mining. Results at the end of paper show the robustness of our approach.

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