Herein, a parallel implementation of Discrete Orthogonal moments on block represented images is investigated. Moments and moment functions have been used widely as features for image analysis and pattern recognition tasks. The main disadvantage of all moment sets, is the high computational cost which is increased as higher-order moments are involved in the computations. In image block representation (IBR) the image is represented by homogeneous areas which are called blocks. The IBR allows moment computation with zero computational error for binary images, low computational error for gray images, low computational complexity, while can achieve high processing rates. The results from parallel implementation on a multicore computer using OpenMP, exhibit significant performance.

在此，研究了离散正交矩在块表示图像上的并行实现。矩和矩函数已被广泛用作图像分析和模式识别任务的功能。所有矩集的主要缺点是高计算成本，随着高阶矩参与计算，该计算成本会增加。在图像块表示（IBR）中，图像由称为块的同质区域表示。IBR允许矩量计算，二进制图像的计算误差为零，灰度图像的计算误差低，计算复杂度低，同时可以实现较高的处理速率。在使用OpenMP的多核计算机上并行实施的结果显示出显着的性能。