Sentence examples for maximum entropy threshold from inspiring English sources

In this paper, maximum entropy threshold image segmentation based on P system is studied.

The algorithm idea is that at first use, the difference method judges whether there is a target object, and if so, get the area of the target object and the image of the region through a 2D maximum entropy threshold binarization processing, which can get the block of the connected regions in the image.

In order to highlight the target (fire), Th1 selects the 2D maximum entropy threshold of the image; it can separate the target and the surrounding background points as far as possible, to facilitate the next step for extraction of the flame and to eliminate the noise points.

For cell counting, an automated segmentation tool (maximum entropy threshold) for ImageJ (Version 1.41o; http://rsbweb.nih.gov/ij/) was used.

First of all, in order to facilitate the application of SRG, median filtering algorithm and background correction algorithm [ 39] are applied on a given image, and then maximum Entropy Threshold [ 40] is applied to produce a binary image A. From the produced binary image A, Direction Cumulative Map H(A) is generated to find seed points.

We set three ranges of voxel intensities and computed by maximum entropy the two delimiting thresholds θ1 and θ2.

A half of the maximum entropy is taken as a threshold between noise-like and tone-like characteristics.

Step 4: maximum entropy method is used to obtain threshold T in the range from 0 to G, then calculate the mean M1,M2 and standard deviation Sd1, Sd2.

We used a multi-threshold version of the maximum entropy approach of (Kapur et al., 1985).

Then, it puts forward that the way of combining maximum entropy method and mathematical criterion selects adaptively optimal threshold for image segmentation by analyzing hue histogram of a set of images.

The threshold is established by using the maximum entropy method [ 16].