Motion-based segmentation and tracking of dynamic radar clutters

Barbaresco, Frédéric; Bonney, S.; Lambert, Jonathan; Monnier, B.

doi:10.1109/icip.1996.560944

Cited by 6 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, an initial sampling frequency to construct a sequence of image frames is selected. Then, we start by computing the mean absolute difference of gray values between two consecutive frames for a sequence of frames, which is given by with (1) where and gray levels of a pixel on the th and 1th frames, respectively. and index and total number of frames of a sequence of images.…”

Section: A Segmentationmentioning

confidence: 99%

“…In related articles about segmentation, Dingle and Morrison [4] presented an algorithm that does not rely on parametric modeling of the observed image, but compares the local distribution with a regional distribution of data. Barbaresco et al [1] proposed an algorithm to differentiate static clutters from dynamic ones based on whether they are moving or not. Namazi and Lipp [10] proposed an extended generalized maximum likelihood (GML) algorithm under the assumption that the Karhunen-Loeve (KL) coefficients of the motion are zero mean and Gaussian random variables.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Endometrium characterization in connection with uterine contraction

Yang

Chung

Tsai

et al. 2001

IEEE Trans. Nucl. Sci.

View full text Add to dashboard Cite

The features of the endometrium are considered important factors in infertility treatment. This paper presents a new approach for estimating the endometrium based on a multiple threshold technique and a general mathematical method. The approach exploits gray-level information to organize and constrain the interpretation of the motion object by a recursive model. The recursive model is employed for threshold optimization of motion information segmentation. This is implemented by repeatedly shrinking the dimension of the maximum potential range of motion with an adaptive threshold throughout the whole process. The values to be estimated comprise motion frequency and thickness. The former is determined by change detection of the number of frame based changes in a sequence of images over a given time period with an appropriate sampling frequency. This can be achieved by a double-increment-of-sampling-frequency mechanism. The latter is the result of the motion object's dimension divided by its extended length. Experimental results indicate that it is possible to accurately estimate the thickness and motion frequency of the endometrium with the proposed algorithm.

show abstract

Section: A Segmentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Endometrium characterization in connection with uterine contraction

Yang

Chung

Tsai

et al. 2001

IEEE Trans. Nucl. Sci.

View full text Add to dashboard Cite

show abstract

“…In [2] the authors use geodesic active contours to perform ;segmentation of thunderstorms from multi sensor data (including interferometric data). However the studied data display quite a low level of noise and, as a matter of fact, active contour methods become less usable whenever noise is important.…”

Section: Choice Of a Methodsmentioning

confidence: 99%