Fast Scene Change Detection Based Histogram

Abstract

This work presents a new approach to detecting the scene change in the successive capture of photographs of a place within equal time interval. This method is based on a gray level histogram of every image. In this method the histogram of an image is processed to modify it for matching with the processed histogram of a reference image. The coefficient of correlation is taken as the measure of matching. As the method does not do any heavy signal processing, and the images are taken successively with a multi-shot digital still camera, it can be applied for real-time processing of such pictures for detection of a scene change. A multi-camera in multi-position approach is also shown to evaluate the change in scene simultaneously from different angles. Both multi-camera and single-camera approaches are compared in detecting a scene change.

Fast Scene Change Detection in Surveillance Systems Using ANOVA on Color Histogram

“…It is not limited by the problem of reflection on highly secular surfaces (such as a mirror surface, or a water surface) where the colors change nondeterministically [7]. The case of insufficient luminance [6] does not influence the final output value either. One remarkable fact is that if only two consecutive images are compared, a very slow scene change over a prolonged period of time is likely to go unnoticed.…”

“…It can be readily visualized from Figure 4. Hence, if the person in Figure 4 (a-g) moves to and fro or keeps standing, the algorithm is able to capture that, which was the main concern in [6].…”

“…The concept of histograms has been focused in Fast Scene Change Detection algorithm [6]. Here, the images are assumed to be captured in RGB color mode.…”

Reconfigurable architecture for computing histograms in real-time tailored to FPGA-based smart camera

“…The algorithm basically extracts image features by deploying a histogram of the pixel edge directions, with the aim of identifying pedestrians in the scene. Even though the histogram software implementation is a simple task used in several light-weight detection algorithms [5], [6], the hardware realization of such algorithm in not a trivial task. A possible hardware oriented histogram extractor has been proposed in [7], [8].…”