scholarly journals Coefficient Combined and Shift and ADD Implementation (CSSI) Based Tunable Multiplierless Rotator Design

2020 ◽  
Vol 9 (4) ◽  
pp. 619-623
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Input Data ◽  
Research Area ◽  
Maximum Resolution ◽  
Coordinate Rotation ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
Number Of Iterations

Signal processing algorithms like Discrete Fourier Transform, Discrete Cosine Transform, and Fast Fourier Transform Transforms find various applications in the field of Image processing, Wireless communication, Robotics, and many others. It covers basically three operations viz. Multiply, Shift and Accumulate. Hence if the input data goes on rising as in cases where high resolution is required the amount of multiply operations also rises significantly. For example the number of complex multiply operations in case of Discrete Fourier Transform is N2 , where N is the number of points. Latency becomes an important issue which needs to be addressed in today’s era as we, humans, thrive for the fastest systems with maximum resolution. To reduce latency we need to either emphasize on reduction in amount of data to be processed or change the processing structure which can affect the overall time to output. Multiplierless techniques for this purpose has been always a research area as it helps in reduction of the later part. Coordinate rotation of digital computer (CORDIC) based techniques are well known for the Multiplierless implementation of the sinusoids. However it carries certain drawbacks viz. large number of iterations and accuracy. This paper provides Coefficient combined & shift and add implementation (CCSSI) based approach for the design of Multiplierless rotators for various transforms for multiple constant rotators as well. The approach improves the range of coefficients with respect to number of adders (the range taken is from 4 to 10 adders) and number of point (the range taken is from 1 to 64 points) compared to the existing approaches and is shown in the results. It also presents a novel tunable Multiplierless architecture.

Fast Algorithmfor Identifying Protein-Coding Regions

2013 ◽  
Vol 647 ◽  
pp. 471-475
Author(s):  
Ling Ke Wang ◽  
Ji Xian Meng ◽  
Hai Peng Zhu ◽  
Xin Zhong Lu
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Research Area ◽  
Genomic Sequences ◽  
Protein Coding ◽  
Signal Noise ◽  
Coding Regions ◽  
Noise Ratio

Identification of protein-coding regions is a hot research area at present. After using mapping methods to turn symbolic genomic sequences into numeric sequences, we need to do the transform to show the period-3 component of protein-coding regions. In this paper, we find twofast algorithms relying on discrete Fourier transform and the extension of Signal Noise Ratio to compute the period-3 component of protein-coding regions.

scholarly journals Comparative Analysis among Discrete Fourier Transform, K-Means and Artificial Neural Networks Image Processing Techniques Oriented on Quality Control of Assembled Tires

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 257
Author(s):  
Alessandro Massaro ◽  
Giovanni Dipierro ◽  
Emanuele Cannella ◽  
Angelo Maurizio Galiano
Keyword(s):  
Image Processing ◽  
Quality Control ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Short Term Memory ◽  
Short Term ◽  
Image Processing Techniques ◽  
Long Short Term Memory ◽  
Artificial Neural ◽  
Processing Techniques

The present paper discusses a comparative application of image processing techniques, i.e., Discrete Fourier Transform, K-Means clustering and Artificial Neural Network, for the detection of defects in the industrial context of assembled tires. The used Artificial Neural Network technique is based on Long Short-Term Memory and Fully Connected neural networks. The investigations focus on the monitoring and quality control of defects, which may appear on the external surface of tires after being assembled. Those defects are caused from tires which are not properly assembled to their respective metallic wheel rim, generating deformations and scrapes which are not desired. The proposed image processing techniques are applied on raw high-resolution images, which are acquired by in-line imaging and optical instruments. All the described techniques, i.e., Discrete Fourier Transform, K-Means clustering and Long Short-Term Memory, were able to determine defected and acceptable external tire surfaces. The proposed research is taken in the context of an industrial project which focuses on the development of automated quality control and monitoring methodologies, within the field of Industry 4.0 facilities. The image processing techniques are thus meant to be adopted into production processes, giving a strong support to the in-line quality control phase.

Design and Implementation of Fast Fourier Transform (FFT) using VHDL Code

2018 ◽  
Vol 6 (8) ◽  
pp. 268
Author(s):  
Akarshika Singhal ◽  
Anjana Goen ◽  
Tanu Trushna Mohapatrara
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Discrete Fourier Transform ◽  
Digital Signal ◽  
Frequency Division ◽  
Signal And Image Processing ◽  
Design And Implementation ◽  
Fft Processor ◽  
Vhdl Code

The Discrete Fourier Transform (DFT) can be implemented very fast using Fast Fourier Transform (FFT). It is one of the finest operation in the area of digital signal and image processing. FFT is a luxurious operation in terms of MAC. To achieve FFT calculation with a many points and with maximum number of samples the MACs requirement could not be matched by efficient hardware’s like DSP. A parallel and pipelined Fast Fourier Transform (FFT) processor for use in the Orthogonal Frequency division Multiplexer (OFDM) and WLAN, unlike being stored in the traditional ROM. The twiddle factors in our pipelined FFT processor can be accessed directly. In this paper, we present the implementation of fast algorithms for the DFT for evaluating their performance. The performance of this algorithm by implementing them on the Xillinx 9.2i Spartan 3E FPGAs  by developing our own FFT processor architecture.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

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