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Accurate and low complex cell histogram generation by bypass the gradient of pixel computation

机译:通过绕过像素计算的梯度,精确和低复杂的细胞直方图

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Histogram of Oriented Gradient (HOG) is a popular feature description for the purpose of object detection. However, HOG algorithm requires a high performance system because of its complex operation set. In HOG algorithm, the cell histogram generation is one of the most complex part, it uses inverse tangent, square, square root, floating point multiplication. In this paper, we propose an accurate and low complex cell histogram generation by bypass the gradient of pixel computation. It employs the bin's boundary angle method to determine the two quantized angles. However, instead of choosing an approximate value of tan, the nearest greater and the nearest smaller of each tan value from the ratios between pixel's derivative in y and x direction are used. The magnitudes of two bins are the solutions of a system of two equations, which represents the equality of the gradient of a pixel and its two bins in both vertical and horizontal direction. The proposed method spends only 30 addition and 40 shift operations to caculate two bins of a pixel. Simulation results show that the percentage of error when reconstructing the differences in x and y direction are always less than 2% with 8-bit length of the fractional part. Additionally, manipulating the precision of gradient magnitude is very simple by pre-defined sine and cosine values of quantized angles. The synthesis results of a hardware implementation of the proposed method occupy 3.57 KGEs in 45nm NanGate standard cell library. The hardware module runs at the maximum frequency of 400 MHz, and the throughput is 0.4 pixel/ns for a single module. It is able to support 48 fps with 4K UHD resolution.
机译:定向梯度(HOG)的直方图是用于对象检测目的的流行特征描述。然而,由于其复杂的操作集,HOG算法需要高性能系统。在猪算法中,小区直方图代是最复杂的部分之一,它使用逆正态,方形,平方根,浮点乘法。在本文中,我们通过绕过像素计算的梯度来提出精确和低复杂的细胞直方图。它采用BIN的边界角度方法来确定两个量化的角度。然而,使用来自在y和x方向上的像素导数之间的比率之间的每个TAN值的每个TAN值的最接近的近似值,而不是选择TAN的近似值。两个箱的幅度是两个方程的系统的解,这代表了像素的梯度和其两个距垂直和水平方向的平等。所提出的方法仅花费30个加法和40个换档操作来缩小两个像素的垃圾箱。仿真结果表明,在重建x和y方向差异时误差的百分比总是小于2 %,具有8位长度的分数部分。另外,通过量化角度的预定义的正弦和余弦值来操纵梯度幅度的精度非常简单。建议方法的硬件实施的合成结果占据了45nm彩酸标准细胞库中的3.57桶。硬件模块以400 MHz的最大频率运行,并且单个模块的吞吐量为0.4像素/ ns。它能够支持4K UHD分辨率的48 FPS。

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