Mohammad Farukh Hashmi

Copy move forgery detection using DWT and SIFT features

Powerful image editing tools like Adobe Photoshop etc. are very common these days. However due to such tools tampering of images has become very easy. Such tampering with digital images is known as image forgery. The most common type of digital image forgery is known as copy-move forgery wherein a part of image is cut/copied and pasted in another area of the same image. The aim behind this type of forgery may be to hide some particularly important details in the image. A method has been proposed to detect copy-move forgery in images. We have developed an algorithm of image-tamper detection based on the Discrete Wavelet Transform i.e. DWT. DWT is used for dimension reduction, which in turn increases the accuracy of results. First DWT is applied on a given image to decompose it into four parts LL, LH, HL, and HH. Since LL part contains most of the information, SIFT is applied on LL part only to extract the key features and find descriptor vector of these key features and then find similarities between various descriptor vectors to conclude that the given image is forged. This method allows us to detect whether image forgery has occurred or not and also localizes the forgery i.e. it tells us visually where the copy-move forgery has occurred.

A Copy Move Forgery Detection to Overcome Sustained Attacks Using Dyadic Wavelet Transform and SIFT Methods

In the present digital world integrity and trustworthiness of the digital images is an important issue. And most probably copy- move forgery is used to tamper the digital images. Thus as a solution to this problem, through this paper we proposes a unique and blind method for detecting copy-move forgery using dyadic wavelet transform DyWT in combination with scale invariant feature transform SIFT. First we applied DyWT on a given test image to decompose it into four sub-bands LL, LH, HL, HH. Out of these four sub-bands LL band contains most of the information we intended to apply SIFT on LL part only to extract the key features and using these key features we obtained descriptor vector and then went on finding similarities between various descriptors vector to come to a decision that there has been some copy-move tampering done to the given image. In this paper, we have done a comparative study based on the methods like a.DyWT b.DWT and SIFT c. DyWT and SIFT. Since DyWT is invariant to shift whereas discrete wavelet transform DWT is not, thus DyWT is more accurate in analysis of data. And it is shown that by using DyWT with SIFT we are able to extract more numbers of key points that are matched and thus able to detect copy-move forgery more efficiently.

A copy-move image forgery detection based on speeded up robust feature transform and Wavelet Transforms

We are currently leaving in a pure digital world where all type of information is mostly stored in digital form. Thus storage of the information is no more a problem and the information can be easily passed on from one place to another in digital format. The big benefit however comes with the hidden loss and in this case it is the tampering of images and videos which has become a matter of serious concern in recent days because of the readily available software tools in the market like Photoshop etc. which can be used by a common person to tamper the image or video for hiding or changing the original contents. Thus for the aforementioned problem, we in this paper propose a series of algorithms which are combination of speeded-up robust feature transforms and Wavelet Transforms. In doing so we will first discuss Speeded-Up Robust Feature (SURF), SURF in combination with Discrete Wavelet Transform (DWT), SURF in combination with Dyadic Wavelet Transform (DyWT). These algorithms are different from the previously proposed algorithm in the manner that they are applied on the entire image to extract features rather than dividing the image into the blocks. From the results obtained we are able to conclude the proposed algorithms are better than their counterparts both in terms of computational complexity and invariance to scale and rotation and also for the combination of attacks.

Analysis and monitoring of a high density traffic flow at T-intersection using statistical computer vision based approach

A reliable traffic flow monitoring and traffic analysis approach using computer vision techniques has been proposed in this paper. The exponential increase in traffic density at urban intersections in the past few decades has raised precious and challenging demands to computer vision algorithms and technological solutions. The focus of this paper is to suggest a statistical based approach to determine the traffic parameters at heavily crowded urban intersections. The algorithm in addition to accurate tracking and counting of freeway traffic also offers high efficiency for determining vehicle count at a high traffic density T-intersection. The system uses Intel Open CV library for image processing. The implementation of algorithm is done using C++. The real time video sequence is obtained from a stationary camera placed atop a high building overlooking the particular T intersection. This paper suggests a dynamic method where each vehicle at a T intersection is passed through a number of detection zones and the final count of vehicles is derived from a statistical equation.

An Optimized Fast Discrete Cosine Transform Approach with Various Iterations and Optimum Numerical Factors for Image Quality Evaluation

In this paper, we have discussed the comparative study of Fast Discrete Cosine Transform (FDCT).The proposed Algorithm investigate the performance evaluation of quantization based Fast DCT and variable block size with different no of iterations based image compression Techniques. This paper has been devoted to improve image compression at low lower no of iterations and higher pixel values. The numerical analysis of such algorithms is carried out by measuring Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR) and CPU processing time. In this paper we have elaborated about the compression ratio with different no iterations. We can evaluate the higher compression ratio results more effectively with lower iteration and higher pixel values than that of quality of image respectively. Image quality will be degraded at higher iteration but compression ratio is better as compare to other algorithms. Different no of iterations and quantized matrix and variable block size are chosen using FDCT for calculating MSE, PSNR and Compression Ratio for achieving the highest image quality and Compression Ratio under the same algorithm. The proposed algorithm significantly raises the PSNR and minimizes the MSE at lower iterations but as above discussion main theory is that Compression Ratio increases at higher iterations and quality of image will not be maintained at higher iterations. We have also calculated the CPU processing time for processing of image compression to find the complexity of algorithm. We have Tested this algorithm two test Images fruit with 512X512 pixel frame and Lena image with 256X256 pixel frames. Thus, we can also conclude that at the same compression ratio the difference between original and decompressed image goes on decreasing, as there is increase in image resolution.

Design and Analysis of DS-CDMA RAKE Receiver Simulator for Wireless Communication

This paper develops a software wireless communication simulator which simulates a Code Division Multiple Access (CDMA). CDMA is a popular technology in cellular systems due to its superior capacity and performance. The simulator is a tool to evaluate these design options and trades in deferent scenarios. The backbone of this system is a wireless CDMA single user link built using Matlab. An efficient method of system modeling is used to speed up the simulations. This simulator can be used to study the performance of a CDMA wireless link with variation in system parameters and channel conditions. In this simulator we can change the attenuation factor and simulate CDMA with RAKE receiver and without RAKE receiver, the transmitted data and received data is show in form of graph, we can compare the received data with and without RAKE receiver for different attenuation factor.

Fuzzy Based Image Forensic Tool for Detection and Classification of Image Cloning

AbstractWith the easy availability of image processing and image editing tools, the cases of forgery have been raised in the last few years. Now days it is very difficult for a viewer and judicial authorities to verify authenticate a digital image. Cloning or copy-move technique is widely used as forgery to conceal the desired object. To hide various type of forgery like Splicing (compositing), cloning (copy-move) etc., various post-forgery techniques like blurring, intensity variation, noise addition etc. are applied. To overcome the mentioned difficulty, a forgery detection tool must comprise of several detection algorithms which work collaboratively to detect all the possible alterations and provide a single decision. This paper presents a universal tool comprising PCA, DWT, DWT-DCT, DWT-DCTSVD, DFT, DCT, DWT-DCT (QCD) techniques used for reduction, feature vector calculation and thus detecting forgery. Due to varied, erroneous, heterogeneous output of different reduction methods, it is very difficult ...

Platform independent Real Time copyright protection embedding and extraction algorithms on Android and Embedded framework

In this paper, we have proposed real time copyright protection algorithm using both visible as well as invisible watermarking schemes and also implementation of real time image processing techniques on Android and Embedded Platform. Smartphone camera technology has provided an efficient way for capturing digital images. Unauthorized sharing of data may lead to illegal usage of data for different purposes. Hence watermarking proves to be an efficient way for preventing piracy and illegal misuse of data. We implement watermarking algorithm using frequency domain techniques of DCT on Real Time captured images. We implement watermark embedding as well as extraction algorithm for digital images. Visible watermarking algorithms are developed by keeping the Android image processing tools as the base structure and invisible watermarking is implemented using OpenCV. On using this system, pre-specified copyright information is embedded directly on the pictures when they are taken. User can also neglect embedding watermark by capturing images using default methods like in the usual way. OpenCV provides a better and efficient interface for implementing complex and computationally expensive algorithms. The watermark extraction algorithm is also implemented using frequency domain analysis. For qualitative analysis, we perform various image distortion operations for calculating the efficiency of our algorithm. These techniques were implemented on Beagleboard-xM using the pre-built android image and OpenCV for Android package. So, this system proves to be an efficient approach for protection of images captured from Android device to prevent piracy.

Comparative Analysis of an Optimal Image Compression Using FDWT at Various Decomposition Level with Different Statistical Numerical Measures for Different Pixel Frame

In this paper, we have also discussed the comparative study of different wavelet-based image compression systems. When wavelet transform is applied to image compression, the chosen wavelet base affects the efficiency of signal strength, pixel values and the quality of the reconstructed image, because the property parameters of different wavelet bases are varied, it is very important to research the correlation between the wavelet base properties and image compression. In this paper, we have discussed various statistical numerical measures and obtained results compared in terms of MSE, PSNR, Normalization and Compression Ratio with lower and higher pixel frames. The main objective of this paper measure the quality of image with statistical numerical measures (PSNR, MSE respectively) using different wavelet families with suitable decomposition level. Different test image with 512 X 512 and 1024 X1024 pixel frames are used to evaluate the performance of image compression. The final choice of optimal wavelet in image compression application depends on image quality, minimum error, optimum PSNR and computational complexity. The experiments are performed using different wavelets at various levels of decomposition. This results show that Discrete Mayer wavelet with second and fourth level decomposition yields better quality for Lena (1024 X 124) and quality has been degrade as lower pixel frame with fruits( 512 X 512)images. Our results provide a good reference for application developers to choose a good wavelet compression system for their application.

Virtual home assistant for voice based controlling and scheduling with short speech speaker identification

With the advancement of interface technologies in smart devices, voice-controlled assistants have quickly gained popularity. These assistants are designed to use voice commands to achieve a more human-friendly interaction. On these lines, we propose a cloud-connected voice based home assistant in this paper. It accepts voice commands to control or monitor devices in a home. It can understand and schedule device operations based on time or sensor data through a simple voice based approach. To enhance its capability, it is designed to identify the speakers. Mel-Frequency Cepstrum Coefficients (MFCC) in combination with other speech features are used as feature vector. We use Vector Quantization (VQ) and Principal Component Analysis (PCA) for dimensionality reduction of the feature vector, followed by Gaussian Mixture Model (GMM) for classification. The validation of the short speech speaker identification is carried out on a set of Indian speakers in an uncontrolled indoor environment. An accuracy greater than 92% is achieved for speech samples as small as 1 second. A database of more than 50 different commands per speaker is also created for validation of the proposed virtual assistant. IBM’s Bluemix and Google’s cloud service is used for speech to text conversion.