Survey on Hardware Implementation of Montgomery Modular

This paper gives the information regarding different methodology for modular multiplication with the modification of Montgomery algorithm. Montgomery multiplier proved to be more efficient multiplier which replaces division by the modulus with series of shifting by a number and an adder block. For larger number of bits, Modular multiplication takes more time to compute and also takes more area of the chip. Different methods ensure more speed and less chip size of the system. The speed of the multiplier is decided by the multiplier. Here three modified Montgomery algorithm discussed with their output compared with each other. The three methods are Iterative architecture, Montgomery multiplier for faster Cryptography and Vedic multipliers used in Montgomery algorithm for multiplication.Here three boards have been used for the analysis and they are Altera DE2-70, FPGA board Virtex 6 and Kintex 7

Survey on Hardware Implementation of Montgomery Modular

This paper gives the information regarding different methodology for modular multiplication with the modification of Montgomery algorithm. Montgomery multiplier proved to be more efficient multiplier which replaces division by the modulus with series of shifting by a number and an adder block. For larger number of bits, Modular multiplication takes more time to compute and also takes more area of the chip. Different methods ensure more speed and less chip size of the system. The speed of the multiplier is decided by the multiplier. Here three modified Montgomery algorithm discussed with their output compared with each other. The three methods are Iterative architecture, Montgomery multiplier for faster Cryptography and Vedic multipliers used in Montgomery algorithm for multiplication.Here three boards have been used for the analysis and they are Altera DE2-70, FPGA board Virtex 6 and Kintex 7

Evaluation of Local Feature Detectors for the Comparison of Thermal and Visual Low Altitude Aerial Images

Local features are key regions of an image suitable for applications such as image matching, and fusion. Detection of targets under varying atmospheric conditions, via aerial images is a typical defence application where multi spectral correlation is essential. Focuses on local features for the comparison of thermal and visual aerial images in this study. The state of the art differential and intensity comparison based features are evaluated over the dataset. An improved affine invariant feature is proposed with a new saliency measure. The performances of the existing and the proposed features are measured with a ground truth transformation estimated for each of the image pairs. Among the state of the art local features, Speeded Up Robust Feature exhibited the highest average repeatability of 57 per cent. The proposed detector produces features with average repeatability of 64 per cent. Future works include design of techniques for retrieval of corresponding regions

A method to improve the computational efficiency of the Chan-Vese model for the segmentation of ultrasound images

Purpose Advanced image segmentation techniques like the Chan-Vese (CV) models transform the segmentation problem into a minimization problem which is then solved using the gradient descent (GD) optimization algorithm. This study explores whether the computational efficiency of CV can be improved when GD is replaced by a different optimization method. Methods Two GD variants from the literature (Nesterov accelerated, Barzilai-Borwein) and a newly developed hybrid variant of GD were used to improve the computational efficiency of CV by making GD insensitive to local minima. One more variant of GD from the literature (projected GD) was used to address the issue of maintaining the constraint on boundary evolution in CV which also increases computational cost. A novel modified projected GD (Barzilai-Borwein projected GD) was also used to overcome both problems at the same time. The effect of optimization method selection on processing time and the quality of the output was assessed for 25 musculoskeletal ultrasound images (five anatomical areas). Results The Barzilai-Borwein projected GD method was able to significantly reduce computational time (average(±std.dev.) reduction 95.82 % (±3.60 %)) with the least structural distortion in the delineated output relative to the conventional GD (average(±std.dev.) structural similarity index: 0.91(±0.06)). Conclusion The use of an appropriate optimization method can substantially improve the computational efficiency of CV models. This can open the way for real-time delimitation of anatomical structures to aid the interpretation of clinical ultrasound. Further research on the effect of the optimization method on the accuracy of segmentation is needed

A concept for movement-based computerized segmentation of connective tissue in ultrasound imaging

This study proposes a novel concept for the computerized segmentation of ultrasound images of connective tissue based on movement. Tendons and ligaments are capable of almost frictionless movement relative to their neighbouring tissues making them good candidates for movement-based segmentation. To demonstrate this concept, a central cross section of the patellar tendon was imaged in the axial plane while movement was generated by manually pulling and pushing the skin close to the imaging area. Maps of internal movement were created for four representative pairs of consecutive images using normalised cross corelation. Thresholding followed by a series of morphological operations (k-clustering, blob extraction, curve fitting) enabled the extraction of the superficial-most tendon boundary. Comparison against manually segmented outputs indicated good agreement against ground truth (average ± STDEV Bhattacharyya distance: 0.170 ± 0.039). In contrast to the more superficial parts of the tissue, the applied method for motion generation did not result in clearly visible movement in the tissue areas deeper in the imaging window. The segmentation of the entire tendon will require movement patterns that involve equally the entire tendon (e.g., generated by a contraction of the in-series muscle). The results of this study demonstrate for the first time that movement mapping can be used for the segmentation of connective tissue. Further research will be needed to identify the optimal way to use motion to complement existing segmentation approaches which are based on signal intensity, texture, and shape features