A Novel Algorithm of Distance Calculation Based-on Grid-Edge-Depth-Map and Gyroscope for Visually-Impaired

Budi Rahmani, Ruliah Ruliah
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Abstract

This paper presented a new algorithm for determining the distance of an object in front of a stereo camera placed on a helmet. By using a stereo camera with a Sum of Absolute Difference with a Sobel edge detector, our previous Grid-Edge-Depth map algorithm could calculate the objects’ distance up to 500 cm. The problem started when a vision disability person used the device with an unfixed stereo camera angle. The unspecified angle caused by the helmet’s movement influenced the distance calculation result. This novel process started with calculating the distance from a Grid-Edge-Depth map considering unfixed angle data of the x-axis from a gyroscope sensor placed on the stereo camera using the trigonometry formula. The angle data used was the x-axis data. The distance measurement results by the system were then computed based on the unfixed angle compared to the actual distance. The test was carried out with three scenarios which required the user to stand at a distance of 100 cm, 125 cm, and 150 cm from a table, chair, or wall, with 30 tests for each scenario. The test results showed an average accuracy of 96.05% with three experimental scenarios, which meant that this machine was feasible to implement.
一种基于网格边缘深度图和陀螺仪的视障距离计算新算法
本文提出了一种确定头盔上立体摄像机前方物体距离的新算法。我们之前的Grid-Edge-Depth地图算法通过使用带有绝对差和的立体相机和Sobel边缘检测器,可以计算出500 cm以内的物体距离。当一个视力有障碍的人使用这个带有不固定立体相机角度的设备时,问题就开始了。头盔运动产生的未确定角度影响了距离计算结果。这个新颖的过程从计算网格边缘深度图的距离开始,考虑放置在立体相机上的陀螺仪传感器的x轴的不固定角度数据,使用三角函数公式。使用的角度数据是x轴数据。然后根据未固定角度与实际距离进行比较,计算系统的距离测量结果。测试分为三种场景,分别要求用户站在距离桌子、椅子或墙壁100厘米、125厘米和150厘米的地方,每种场景有30个测试。测试结果表明,三种实验场景下的平均准确率为96.05%,表明该机器是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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