Symmetry Filters Research Articles

Implementation of block-based diagonal and quadrantal symmetry type 2D-FIR filter architectures using DA technique

The efficient architectures of Two-Dimensional (2D) Finite Impulse Response (FIR) filters are proposed for image processing applications. The performance metrics such as power consumption, area, and delay of the architectures can be optimized using VLSI design. The 2D FIR filter architectures can be implemented using parallel or block processing to increase the filter throughput and to prune the number of clock cycles required for image processing. The symmetry in the filter coefficients decreases the number of multipliers, whereas the multiplier block is very complex and a power-consuming block in the filter architecture. In this work, two types of symmetric architectures such as diagonal symmetry and quadrantal symmetry filters are proposed. The remaining multipliers required for the filter architecture are replaced by Distributed Arithmetic (DA) logic. The memory-based DA reduces the LUT size and hence the area, power, and delay are reduced in the filter architecture. Block processing, symmetry, and DA concepts are introduced here to optimize the 2D FIR filter architecture. The proposed architectures are implemented in 45 nm CMOS technology using Cadence Genus Synthesis tools and area, delay, power, Area-Delay Product (ADP), and Power-Delay Product (PDP) results are obtained and compared with state-of-the-art works. The ADP value of the proposed diagonal symmetry architecture is decreased by a maximum of 73.34 %, and a minimum of 20.39 %, and the PDP value is decreased by a maximum of 90.28 %, and a minimum of 21.27 % when compared to the existing works. The ADP and PDP values of the proposed quadrantal symmetry are decreased by a minimum of 23.62 %, and 27.74 % when compared to existing works, respectively.

Implementation of Low Power Generic 2D FIR Filter Bank Architecture Using Memory-based Multipliers

In this paper, a generic filter bank architecture for 2D FIR filter is proposed using block processing, symmetry in the filter coefficients, and memory-based multipliers. The different symmetry filters are considered as sub-filters of the filter bank to decrease the number of multipliers and the desired filter can be selected using control logic to reduce the power consumption. The block processing is incorporated to increase the throughput of the filter. Due to this block processing, memory sharing and memory reuse are achieved to optimize the architecture in terms of area, memory, and power. In each filter, the conventional multipliers are replaced with Distribute Arithmetic (DA) based memory multipliers to decrease the delay, power, and area of each sub-filter. The proposed design is coded by Verilog HDL and synthesized using Cadence Genus tools in 45 nm technology. The physical design is carried out using Cadence Innovus tools. The proposed design results are compared with state-of-the-art works.

A novel filter-bank architecture of 2D-FIR symmetry filters using LUT based multipliers

In this paper, a novel block-based generic filter bank architecture is proposed for various Two Dimensional (2D) symmetry Finite Impulse Response (FIR) filers. It is implemented to prune the area, storage memory, and power consumption of the filter bank. Four 2D symmetrical FIR filter architectures are implemented and explored along with a general filter (without symmetry). The symmetry in coefficients of the filter reduces the number of multiplier blocks (most power-hunger blocks) required for the structure. Hence, a major part of the total power consumption is decreased. Block processing is introduced to improve the throughput of the filter bank. The memory sharing and memory reuse concepts are incorporated to reduce the storage memory of the entire filter bank. Finally, the conventional multiplication process is replaced with memory-based dual-port Look-Up-Table (LUT)-Distributed Arithmetic (DA) multipliers to minimize the power and area of each sub-filter of the filter bank. A generic filter bank architecture is implemented and synthesized in CMOS 45 nm generic library using Genus tools and physical design is carried out by Innovus tools from Cadence. The final layout of the design is generated using proper floor planning, placement, and routing in physical design. The results are compared with the state-of-art works of 2D FIR filters. The significantly improved results are reported in terms of area, power, delay, and memory.

Symmetry Incorporated Cost-Effective Architectures for Two-Dimensional Digital Filters

Professor Fettweis as far back as 1977 published a paper generalizing McClellan transformation to obtain circular symmetry in 2-D and spherical, hyper-spherical symmetries in multidimensional digital filters [1]. This survey paper presents stateof-the-art two-dimensional (2-D) VLSI digital filter architectures possessing various symmetries in the filter magnitude response. Preceding the symmetry structures, a generalized formulation is given that allows the derivation of various new 2-D VLSI filter structures of any order without global broadcast. Following this, two types (namely, Type 1 [20] and Type 3 [21], [25], [26]) of cost-effective 2-D magnitude symmetry filter architectures possessing diagonal, four-fold rotational, quadrantal, and octagonal symmetries with reduced number of multipliers are given. By combining the identities of the Types-1 and 3 symmetry filter structures, multimode 2-D symmetry filters which enable the above four symmetry modes are discussed. The Type-1 and Type-3 multimode filters can result in a 65.3% cost reduction in terms of number of multipliers compared with the sum of the multipliers of the four individual Type-1 symmetry filter structures studied in this paper. Furthermore, Type-3 has shorter critical path than Type-1 multimode filter. The paper is concluded with the presentation of a 2-D filter design example and a corresponding structure.

Near‐infrared and visible‐light periocular recognition with Gabor features using frequency‐adaptive automatic eye detection

Periocular recognition has gained attention recently due to demands of increased robustness of face or iris in less controlled scenarios. We present a new system for eye detection based on complex symmetry filters, which has the advantage of not needing training. Also, separability of the filters allows faster detection via one-dimensional convolutions. This system is used as input to a periocular algorithm based on retinotopic sampling grids and Gabor spectrum decomposition. The evaluation framework is composed of six databases acquired both with near-infrared and visible sensors. The experimental setup is complemented with four iris matchers, used for fusion experiments. The eye detection system presented shows very high accuracy with near-infrared data, and a reasonable good accuracy with one visible database. Regarding the periocular system, it exhibits great robustness to small errors in locating the eye centre, as well as to scale changes of the input image. The density of the sampling grid can also be reduced without sacrificing accuracy. Lastly, despite the poorer performance of the iris matchers with visible data, fusion with the periocular system can provide an improvement of more than 20%. The six databases used have been manually annotated, with the annotation made publicly available.

Skeleton-based intrinsic symmetry detection on point clouds

We present a skeleton-based algorithm for intrinsic symmetry detection on imperfect 3D point cloud data. The data imperfections such as noise and incompleteness make it difficult to reliably compute geodesic distances, which play essential roles in existing intrinsic symmetry detection algorithms. In this paper, we leverage recent advances in curve skeleton extraction from point clouds for symmetry detection. Our method exploits the properties of curve skeletons, such as homotopy to the input shape, approximate isometry-invariance, and skeleton-to-surface mapping, for the detection task. Starting from a curve skeleton extracted from an input point cloud, we first compute symmetry electors, each of which is composed of a set of skeleton node pairs pruned with a cascade of symmetry filters. The electors are used to vote for symmetric node pairs indicating the symmetry map on the skeleton. A symmetry correspondence matrix (SCM) is constructed for the input point cloud through transferring the symmetry map from skeleton to point cloud. The final symmetry regions on the point cloud are detected via spectral analysis over the SCM. Experiments on raw point clouds, captured by a 3D scanner or the Microsoft Kinect, demonstrate the robustness of our algorithm. We also apply our method to repair incomplete scans based on the detected intrinsic symmetries.

Symmetry filters using optical correlation and convolution

We describe a novel method based on optical cross-correlation and autoconvolution for the selective enhancement of image components with specific symmetry. Such a symmetry filter can operate in real time by using nonlinear optical four-wave mixing. Instead of correlating with a set of preselected references, the input picture is correlated with its own rotated version, which is generated by simple optics. Any patterns that are invariant under the rotation will exhibit strong correlation signals.

Design of two-dimensional recursive digital filters

The present paper develops a design technique for approximating nonseparable frequency characteristics by sums and products of transfer functions. This approximation is called the piecewise separable decomposition of the characteristic. In the design technique, the desired filter with half-plane symmetry (radial symmetry) is obtained by shifting a low-pass characteristic in the frequency domain, and by combining these shifted characteristics. Also the paper includes design approaches for the four-quadrant symmetry filters. Two examples illustrate the technique of the paper.