Segmentation with Invisible Keying Signal

نویسنده

  • Moshe Ben-Ezra
چکیده

Chroma keying is the process of segmenting objects from images and video using color cues. A blue (or green) screen placed behind an object during recording is used in special effects and in virtual studios. The blue color is later replaced by a different background. A new method for automatic keying using invisible signal is presented. The advantages of the new approach over conventional chroma keying include: (i) Unlimited color range for foreground objects. (ii) No foreground contamination by background color. (iii) Better performance in non uniform illumination. (iv) Features for generating refraction and reflection of dynamic objects. The method can be used in real-time and no user assistance is required. New design of Catadioptric camera and a single chip sensor for keying is also presented.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Adaptive Segmentation with Optimal Window Length Scheme using Fractal Dimension and Wavelet Transform

In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different fr...

متن کامل

An Adaptive Segmentation Method Using Fractal Dimension and Wavelet Transform

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...

متن کامل

An Adaptive Segmentation Method Using Fractal Dimension and Wavelet Transform

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...

متن کامل

A Time-Frequency approach for EEG signal segmentation

The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...

متن کامل

An Improved Automatic EEG Signal Segmentation Method based on Generalized Likelihood Ratio

It is often needed to label electroencephalogram (EEG) signals by segments of similar characteristics that are particularly meaningful to clinicians and for assessment by neurophysiologists. Within each segment, the signals are considered statistically stationary, usually with similar characteristics such as amplitude and/or frequency. In order to detect the segments boundaries of a signal, we ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2000