Robert D. Dony

Edge detection on color images using RGB vector angles

This paper introduces a new edge detection approach for color images. The method is based on the calculation of the vector angle between two adjacent pixels. Unlike Euclidean distance in RGB space, the vector angle distinguishes differences in chromaticity, independent of luminance or intensity. It is particularly well suited to applications where differences in illumination are irrelevant. Both metrics were implemented as modified Roberts edge operators to determine their effectiveness on an artificial image. The Euclidean method found edges across both luminance and chromatic boundaries whereas the vector angle method detected only chromatic differences.

Strength pareto particle swarm optimization and hybrid ea-pso for multi-objective optimization

This paper proposes an efficient particle swarm optimization (PSO) technique that can handle multi-objective optimization problems. It is based on the strength Pareto approach originally used in evolutionary algorithms (EA). The proposed modified particle swarm algorithm is used to build three hybrid EA-PSO algorithms to solve different multi-objective optimization problems. This algorithm and its hybrid forms are tested using seven benchmarks from the literature and the results are compared to the strength Pareto evolutionary algorithm (SPEA2) and a competitive multi-objective PSO using several metrics. The proposed algorithm shows a slower convergence, compared to the other algorithms, but requires less CPU time. Combining PSO and evolutionary algorithms leads to superior hybrid algorithms that outperform SPEA2, the competitive multi-objective PSO (MO-PSO), and the proposed strength Pareto PSO based on different metrics.

An FPGA Implementation of the LMS Adaptive Filter for Audio Processing

This paper proposes three different architectures for implementing a least mean square (LMS) adaptive filtering algorithm, using a 16 bit fixed-point arithmetic representation. These architectures are implemented using the Xilinx multimedia board as an audio processing system. The on-board AC97 audio codec is used for audio capture/playback, and the Virtex-II FPGA chip is used to implement the three architectures. A comparison is then made between the three alternative architectures with different filter lengths for performance and area. Results obtained show an improvement by 90% in the critical part of the algorithm when a hardware accelerator is used to perform it over a pure software implementation. This results in a total speed up 3.86times. However, using a pure hardware implementation results in a much higher performance with somewhat lower flexibility. It shows a speed up close to 82.6times over the software implementation

Differential evolution with Powell's direction set method in medical image registration

Powells direction set method (PDSM) is widely used in image registration. However, its performance is found to be strongly dependent on the initial solution. In this paper we propose a novel combination of PDSM with initialization by the differential evolution genetic algorithm. To further improve the convergence, a multi-resolution approach is taken. Mutual information is chosen as the error metric for this investigation. The results presented show that this proposed method does significantly improve the performance of PDSM and it is efficient and robust.

Window Based Prototype Filter Design for Highly Oversampled Filter Banks in Audio Applications

This paper describes a window based method for designing near perfect-reconstruction prototype filters for highly oversampled, complex modulated filter banks. The design method extends some well-known simple methods for critically sampled filter banks to the over-sampled case and to the case of different length analysis and synthesis filters. This design method is simple and effective for designing a large range of filter bank configurations. The design method is particularly useful in developing audio applications using oversampled filter banks where the target systems requirements are highly variable. The simplicity and flexibility of the design method means that this one method can be used to generate multiple prototype filters as the application requirements change

An adaptive encryption based genetic algorithms for medical images

This paper presents a novel efficient symmetric encryption technique that can be applied to medical images. It uses genetic algorithm which makes it highly adaptive. Standard DI-COM images are segmented into a number of regions based on pixel intensity and entropy measurements. The novelty of the selective encryption method lies in the use of several encryption algorithms with variable key lengths to control the processing time required for the encryption process and the robustness quality. Encryption processing time, robustness of the encrypted image and the side information required for transmission of the decryption key are the main parameters for optimization. The trade-off among them stems from the variation in processing time with the key length of encryption algorithm, image size, number of regions and the side information to reduce processing time while maintaining a high level of robustness.

Evaluation of image corner detectors for hardware implementation

We analyze a number of corner detection algorithms and identify the advantages and disadvantages of each algorithm to evaluate their suitability for hardware implementation. We implemented three popular corner detectors, Plessy, Wang-Brady, and SUSAN, in software and compared them on the basis of their stability, accuracy, speed and computational requirements. The Plessy algorithm was found to have good stability and accuracy, but suffered from a large computational cost. The SUSAN method required the least computational resources and would therefore be suitable for implementation on a simple FPGA platform. However, it did not perform well on real world images. The Wang-Brady method was found to have better stability than SUSAN but worse than the Plessy algorithm while having a lower computational cost than Plessy and a higher cost than that for SUSAN. Despite the higher computational requirements, we conclude that the Plessy algorithm, because of its significantly better performance, is the most appropriate algorithm for hardware implementation.

Shading- and highlight-invariant color image segmentation using the MPC algorithm

Anew color image segmentation algorithm is presented in this paper. This algorithm is invariant to highlights and shading. This is accomplished in two steps. First, the average pixel intensity is removed form each RGB coordinate. This transformation mitigates the effects of highlights. Next, the Mixture of Principal Components algorithm is used to perform the segmentation. The MPC is implicitly invariant to shading due to the inner vector product or vector angle being used as similarity measure. Since the new coordinate system contains negative numbers, it is necessary to modify the MPC algorithm since in its original form it does not distinguish between positive and negative color space coordinates. Results on artificial and real images illustrate the effectiveness of the method. Finally, the use of the total within-cluster variance is investigated as possible criterion for selecting the number of clusters for the new algorithm.

Improving the Security of the Medical Images

Applying security to the transmitted medical images is important to protect the privacy of patients. Secure transmission requires cryptography, and watermarking to achieve confidentiality, and data integrity. Improving cryptography part needs to use an encryption algorithm that stands for a long time against different attacks. The proposed method is based on number theory and uses Chinese remainder theorem as a backbone. This approach achieves high level of security and stands against different attacks for a long time. On watermarking part, the medical image is divided into two regions: a region of interest (ROI) and a region of background (ROB). The pixel values of the ROI contain the important information so this region must not experience any change. The proposed watermarking technique is based on dividing the medical image in to blocks and inserting the watermark to the ROI by shifting the blocks. Then, an equivalent number of blocks in the ROB are removed. This approach can be considered as lossless since it does not affect on the ROI, also it does not increase the image size. In addition, it can stand against some watermarking attacks such cropping, and noise.

An efficient scheduling methodology for heterogeneous multi-core processor systems

This paper outlines a scheduling methodology for signal processing applications onto heterogeneous multiprocessor systems. The goal is to efficiently schedule an application in the form of direct acyclic graphs (DAG), onto a heterogeneous processor environment. The solution is to use a variety of optimization techniques based on greedy methods and meta-heuristic methods to solve the problem. Results obtained indicate that the system is efficient in placing tasks to create an optimal schedule.