DA‐Based Circuits for Inner‐Product Computation

Mehendale, Mahesh; Sharma, Maya; Meher, Pramod Kumar

doi:10.1002/9781119206804.ch3

Cited by 2 publications

(1 citation statement)

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“…Several methods have been used to assist NCC for reducing its searching and computing times in image matching, such as the pyramid method [3,7]. In addition, many parallel algorithms of the inner-product have been published that can perform fast cross-correlation for NCC [16,17], where the Distributed Arithmetic (DA) with look-up table has not multiplication, but needs much Read-Only Memory (ROM) [18].…”

Section: Introductionmentioning

confidence: 99%

The Algorithm and Structure for Digital Normalized Cross-Correlation by Using First-Order Moment

Pan

Xia

et al. 2020

Sensors

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Normalized cross-correlation is an important mathematical tool in digital signal processing. This paper presents a new algorithm and its systolic structure for digital normalized cross-correlation, based on the statistical characteristic of inner-product. We first introduce a relationship between the inner-product in cross-correlation and a first-order moment. Then digital normalized cross-correlation is transformed into a new calculation formula that mainly includes a first-order moment. Finally, by using a fast algorithm for first-order moment, we can compute the first-order moment in this new formula rapidly, and thus develop a fast algorithm for normalized cross-correlation, which contributes to that arbitrary-length digital normalized cross-correlation being performed by a simple procedure and less multiplications. Furthermore, as the algorithm for the first-order moment can be implemented by systolic structure, we design a systolic array for normalized cross-correlation with a seldom multiplier, in order for its fast hardware implementation. The proposed algorithm and systolic array are also improved for reducing their addition complexity. The comparisons with some algorithms and structures have shown the performance of the proposed method.

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