An assisting model for the visually challenged to detect bus door accurately

Visually impaired individuals are increasing and as per global statistics, around 39 million are blind, and 246 million are affected by low vision. Even in India, as per the recent reviews, over 5 million visually challenged people are present. Authors performed a survey of some critical problems the visually challenged people faced in India from the centre for visually challenged (CVC) School established by UVSM Hospitals. Among the major problems identified through survey, most of these persons prefer carrying out their tasks independently, and depend on public transport buses for migration. However, critical sub-problems being faced include; bus door identification and identifying the bus route number accurately. This article aims to provide solutions in helping visually challenged individuals to identify exact bus that drives them to their destination, its door, bus number, and the path for boarding bus. A video sequence of current scenario would be sent to mobile, in which the actual processing of image is carried out. After the video sequence processing, generated output is a voice message that specifies the bus's location, door, and exact information of the bus number along the road path directly to the user using a wireless device aiming foa a low-cost solution

視覚障害者のバス利用支援のための画像処理を用いたカメラ視点識別に関する研究

The bus identification using smartphone camera is one useful application for blind people who travel independently in daily life. Although, many existing researches have focused on the bus identification by using image processing, those researches did not concern the viewpoint of image before the oncoming bus appear in the image. This research proposes the definition and classification of suitable viewpoint of bus-waiting for aiding blind people, which is proposed into three conditions as following: 1) non-congested traffic; 2) congested traffic; and 3) obstacles detection along the road. The first condition of non-congested traffic classified the viewpoint using the road area consideration, which this research applied the Rotational Invariant of Uniform of Local Binary Pattern technique for extracting the road area, and the Back-propagation of Artificial Neural Network for the viewpoint classification. The second condition is congested traffic, which appears a huge number of car in the image. The distribution of car in the image was calculated by many features, which the optimized results showed that seventeen selected features and Random Forest classifier provided the high performance. For third condition, the obstacles along the road will be consideration in case of non-congested traffic. This research combined many existing techniques of image processing to detect the obstacles along the road, which consisted of two main processes: 1) obstacle’s location detection and 2) obstacle’s height estimation. The proposed detected technique can implement in the daylight condition with high performance. According to experimental results, the high performance have shown by 98.56%, 86.00% for non-congested and congested traffics, respectively. Moreover, the performance of obstacles position detection and height estimation were shown by 91.20%, 86.00%, respectively. Based on these results, these are feasible to apply for viewpoint classification in order to assist blind people, who are independently waiting for the bus.九州工業大学博士学位論文 学位記番号:生工博甲第356号 学位授与年月日:令和元年9月20日1. Introduction|2. Previous Studies|3. Suitable Viewpoint Definition of Waiting for the Bus|4. Classification of Viewpoints while Waiting for the Bus in Situation of Non-Congested Traffic|5. Classification of Viewpoints while Waiting for the Bus in Situation of Congested Traffic|6. Obstacle Detection along the Road|7 Conclusions and Future Work九州工業大学令和元年