Prachi Natu

Transform based face recognition with partial and full feature vector using DCT and Walsh transform

This paper presents, efficient transform based face recognition technique which considers full and partial feature vector of an image. 2D-DCT and Walsh transform is applied on the resized image of size 128x128, to obtain its feature vector. Partial feature vector is obtained by selecting 75% rows and columns of feature vector, 50% rows and columns of feature vector and so on. The smallest size of partial feature vector is selected as 4x4. Proposed technique is tested on two different databases. Georgia Tech Face Database contains JPEG color images and Indian Face Database contains Bitmap color images of varying size. Recognition rate is calculated for varying size of selected feature vector using DCT and Walsh transform and compared. Also computational complexity in terms of number of CPU units is compared in both the cases: with full feature vector and with partial feature vector. Results show that, Walsh transform gives better recognition rate than DCT and number of CPU units required using 2D- Walsh transform is almost 9 times less than that of required by using 2D-DCT. This is because the multiplications required in Walsh transform are zero.

Performance Comparison of Speaker Identification Using DCT, Walsh, Haar on Full and Row Mean of Spectrogram

ABSTRACT This paper aims to provide different approaches to text dependent speaker identification using various transformation techniques such as DCT, Walsh and Haar transform along with use of spectrograms. Set of spectrograms obtained from speech samples is used as image database for the study undertaken. This image database is then subjected to various transforms. Using Euclidean distance as measure of similarity, most appropriate speaker match is obtained which is declared to be identified speaker. Each transform is applied to spectrograms in two different ways: on full image and on Row Mean of an image. In both the ways, effect of different number of coefficients of transformed image is observed. Further, comparison of all three transformation techniques on spectrograms in both the ways shows that numbers of mathematical computations required for Walsh transform is much lesser than number of mathematical computations required in case of DCT on spectrograms. Whereas, use of Haar transform on spectrograms drastically reduces the number of mathematical computation with almost equal identification rate. Transformation techniques on Row Mean give better identification rate than transformation technique on full image.

Halftone Image Data Compression Using Kekre’s Fast Code Book Generation (KFCG) Algorithm for Vector Quantization

Halftone technique is well known for printing where binary data is required. 8:1 compression ratio is achieved by half toning method. To get higher compression ratio the same technique can be used in image processing. In our earlier work different half toning operators are proposed. The half toning operator of size 3X3 which effectively take only one tap operation. Hence the computational complexity and memory space is reduced. For further compression of the image data Vector Quantization technique is used. Vector Quantization technique itself gives very high compression ratio. To avoid time and computational complexity Kekre’s Fast Code Book Generation (KFCG) algorithm is used. In this paper we have used 8, 16, 32, 64, 128 and 256 codebook sizes are used. The pixel group of 2X2 size is used. The experimental results are obtained for various images. For image data compression and image quality measurement, we have used Compression Ratio and Mean Square Error as measuring parameters respectively. We have got result with good Compression Ratio and acceptable image quality. This proposed combination of two compression technique is suitable for video data streaming, where low bit rate for data transmission is the major constraint.

Performance superiority of hybrid DKT-DCT wavelet compared to DKT, DCT individual transforms and their wavelets in image compression

This paper proposes simple and novel image compression method using transforms. Discrete cosine Transform (DCT) and Discrete Kekre Transform (DKT) are applied on image individually. Wavelet transform of DCT and DKT is generated using Kekres algorithm of wavelet generation. Wavelet transform gives better energy compaction than individual transform. It is reflected in reconstructed image quality of wavelet transforms. Further hybridization of two transform is used and hybrid wavelet transform using DKT and DCT is generated and applied on images. It combines properties of both, Kekre transform and DCT. Hybrid wavelet transform gives lesser error than wavelet transform and individual orthogonal transform.

ImageCompression Using Real Fourier Transform, Its Wavelet Transform And Hybrid Wavelet With DCT

This paper proposes new image compression technique that uses Real Fourier Transform. Discrete Fourier Transform (DFT) contains complex exponentials. It contains both cosine and sine functions. It gives complex values in the output of Fourier Transform. To avoid these complex values in the output, complex terms in Fourier Transform are eliminated. This can be done by using coefficients of Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST). DCT as well as DST are orthogonal even after sampling and both are equivalent to FFT of data sequence of twice the length. DCT uses real and even functions and DST uses real and odd functions which are equivalent to imaginary part in Fourier Transform. Since coefficients of both DCT and DST contain only real values, Fourier Transform obtained using DCT and DST coefficients also contain only real values. This transform called Real Fourier Transform is applied on colour images. RMSE values are computed for column, Row and Full Real Fourier Transform. Wavelet transform of size N2xN2 is generated using NxN Real Fourier Transform. Also Hybrid Wavelet Transform is generated by combining Real Fourier transform with Discrete Cosine Transform. Performance of these three transforms is compared using RMSE as a performance measure. It has been observed that full hybrid wavelet transform obtained by combining Real Fourier Transform and DCT gives best performance of all. It is compared with DCT Full Wavelet Transform. It beats the performance of Full DCT Wavelet transform. Reconstructed image quality obtained in Real Fourier-DCT Full Hybrid Wavelet Transform is superior to one obtained in DCT, DCT Wavelet and DCT Hybrid Wavelet Transform.

A Review on Organizational Modules of Autonomous Vehicles

Autonomous vehicle technology has seen immense breakthroughs in recent years. Currently existing models, however, are inoperable in moderate to highly adverse environments, clearly indicating a need for refinement in all three key aspects of a self-driving vehicle, which are navigation, system interconnection and security systems. A self-driving vehicle must be able to traverse difficult terrain in adverse weather conditions and reach its destination accurately before its navigation systems can be deemed fit for public usage. Self-driving vehicles must be interconnected and must work efficiently in cooperation to minimize traffic and time delay in travel while also having adequate backup systems to cope with interconnection and network failures. In this paper are reviewed multiple different approaches to the solution of each of these aspects of a self-driving car. Based on the inferences of this review, the areas where improvement could result in more breakthroughs which could make autonomous vehicle technology get implemented in the near future are highlighted.

Digital Image Compression using Hybrid Transform with Kekre Transform and Other Orthogonal Transforms

This paper presents image compression technique using hybrid transform. Concept of hybrid wavelet transform can be extended to generate hybrid transform. In hybrid wavelet transform first few rows represent global features of an image and remaining rows represent local features of an image. In Hybrid wavelet matrix rows contributing to global characteristics can be varied. In the limiting case by taking kronecker product of to orthogonal component transforms, hybrid transform is generated where all rows of transform matrix represent global features and no local features are present. This hybrid transform matrix is then applied on color image. High frequency contents of transformed image are eliminated and only low frequency contents are retained to get compressed image. RMSE is calculated at different compression ratios to check the performance of hybrid transforms. Various orthogonal transforms like DCT,Walsh, Slant, Hartley, Real-DFT and DST are combined with Kekre transform to generate hybrid transforms. DKT-DCT gives better image quality and lower RMSE than other pairs formed with DKT. Component size 32-8 i.e.32x32(Kekre Transform) and 8x8 (DCT) gives best results than other possible size combinations like 8-32,16-16 and 64-4.