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It has been employed to segment the images and extract objects.
On the other hand, automatic video segmentation methods extract objects without initial interactions [14 17].
In this paper, we propose a novel algorithm to extract objects as well as humans from video sequences automatically.
Then, by comparing the flash image with the no-flash one, color and intensity differences are obtained to extract objects.
They extract objects in the first frame based on users' markings, and then track the objects in subsequent frames using color, position, and temporal cues.
In this paper, a novel technique is developed to extract objects from video sequences based on spatiotemporal independent component analysis (stICA) and multiscale analysis.
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In the feature extraction step, we extract object features such as the color, texture, and shape.
Comparative experiments demonstrate that the proposed edge detection algorithm can extract object boundaries and inhibit non-boundary edges caused by textures on object surfaces.
The result using another airborne video is shown in Figure 17, which further demonstrated that our method can better extract object sizes.
GEOBIA starts by segmenting the image grouping together pixels into objects and next uses a wide range of object properties to classify the objects or to extract object's properties from the image.
Lastly, adaptive immune factors in the last layer will extract object and background antigens from all the banded blurred image antigens, and design the optimal immune field of every adaptive immune factors.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com