Flicker is the most common and an intolerable blemish present in signal processing world that leads to distortion in the transmitted frame of a video string. To dodge such misinterpretations a technique for detection of the flickering frame in a video is depicted in this research. Earlier methods were based on removing flicker by calculating the threshold of the consecutive frame difference and then finding the flickering frame. The proposed method in this research includes finding flickering frame using neural network concept. Therefore, the advantage of the practice disclosed here is that it removes the tedious calculation part of the threshold value and thereby the computational part becomes easier with added accurate result.
Object detection, is an important element of various computer vision areas, such as image retrieval, shot detection, video surveillance, etc. which require automatic segmentation or location of regions of interest in images which can be further analyzed by more computationally demanding techniques to produce a correct interpretation. This paper explores the possibility of performing this task of object detection in any general environment using the intensity pattern information in individual channels of YCbCr Color space. It was observed that prominent objects could be easily and efficiently detected by the algorithm irrespective of the environment they are kept in. The efficiency of the algorithm boasts the possibilities of further simplistic models for the invigorating task as of image detection for complicated computer vision applications.
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