The efforts spent on the development of assistive technologies has led researches to explore many existing techniques as computer vision, image processing, etc. and apply them as embedded solutions to help people with several types of disabilities, including visual impairment. Embedded navigation systems for visually impaired people (VIP) often use RGB-D cameras to retrieve depth information from surroundings and present them as gray images with depth represented by gray level or black pixels if depth couldn't be estimated, which can be fixed by mathematical morphology. Morphological filters must be efficient to solve the problem and fast to avoid impact on performance. This paper presents an approach for automatic generation and optimization of low complexity and low error morphological filters to fix depth image’s unknown distances based on NSGA-II and Cartesian Genetic Programming. Experiments were performed using two different error metrics and results showed that the presented approach managed to generate and optimize feasible morphological filters that fit within embedded navigation systems for VIP.

中文翻译：

---

嵌入式导航系统深度图像多目标形态滤波器自动生成的进化方法

开发辅助技术的努力促使研究人员探索了许多现有技术，如计算机视觉、图像处理等，并将它们作为嵌入式解决方案应用，以帮助包括视力障碍在内的多种类型的残疾人。用于视障人士 (VIP) 的嵌入式导航系统通常使用 RGB-D 摄像头从周围环境中检索深度信息，并将其呈现为灰度图像，深度由灰度表示，如果无法估计深度，则可以通过黑色像素来修复。数学形态学。形态过滤器必须高效解决问题，快速避免影响性能。本文提出了一种基于NSGA-II和笛卡尔遗传编程的低复杂度和低误差形态滤波器的自动生成和优化方法，以修复深度图像的未知距离。使用两种不同的误差度量进行了实验，结果表明，所提出的方法设法生成和优化了适合 VIP 嵌入式导航系统的可行形态过滤器。