Detection of Small Objects With Low Contrast in Image Signal Processing

This paper presents an effective approach to the detection of small objects by employing frequency transformation method. In this work, moving objects with small size and low contrast are first detected from an image sequence which was captured from an image from the database. The proposed detection system includes two main modules, region of interest locating and contour extraction. A novel neighboring encoding technique along with the image differencing technique is devised here to effectively reduce noise which usually affects the performance of detection results, especially for small objects. Next, we find the bounded rectangles enclosing the denoised images, which in turn generate region of interest. Experimental results validate that the proposed approach is indeed feasible and effective in detecting objects with small size and low contrast.