Recognition Methods of Housing Vacancy Based on Digital Image Processing

This paper, based on computer image processing technology, researches the statistical method to the housing vacancy rate, making use of residential building at night images. This method needs three steps, the first step is image preprocessing, to enhance, denoise and correct the building image in the night scene, using the methods of histogram equalization, wavelet transform, the Radon transform and the connection point. The second step is the image threshold segmentation, to segment the images of dark and bright windows with the fixed threshold method and improve the between-cluster variance method. The third step is through the image fusion technology, making use of closed area centroid coordinates in the horizontal and vertical coordinates from big to small order, then determining the location and the number of dark and bright windows, and finally concluding the vacancy rate. Finally, to achieve the hybrid programming of Matlab and Visual c++ by using the application of Matrix, we realize the above functions. We make comparative analysis to the conclusions from this method, and by comparing with the present commonly used methods, we verify the feasibility of the proposed method in this paper.