In this study, we will investigate a new image signal processing method in order to develop a highly useful walking support device for visually impaired people. Visually impaired people walk independently using assistive devices. Currently, there are many support devices that use object detection and object recognition using deep learning, but there are still no highly useful devices. The smallest unit constituting an image signal is a pixel. Adjacent pixels are correlated with each other. The positional relationship of pixels expresses the features of objects, and scenery in the image. Autoregressive (AR) model is a regression analysis method used to analyze time-series signals. AR models are one of the basic methods for signal processing for speech recognition and control. Furthermore, in image signal processing, it can be used as a signal processing method when data has some kind of order, such as texture feature extraction, contour processing, and video processing. In this experiment, we converted the pixel array of the image signal into a one-dimensional time-series signal and process the signal. We tried to identify objects or regions within images. The method proposed in this study may be used to extract “Point of Interest” (POI) and “Point of Reference” (POR), which are important information for visually impaired people.