### Clean-up > Reject Features

Removes objects or fills holes based on their selected parameters being above or below a specified threshold. Parameter options include area, eccentricity, convex area/area ratio, and many more. Neighborhood conditionals are also optional, where features will only be removed if they meet both the parameter and neighborhood criteria.

### 1. Measurement

Determines the measurement that will be considered for each features potential rejection. Features will be rejected based on whether they are above or below the measurement threshold you specify.

**Area:**Area of each feature.**Area Fraction:**Area fraction occupied by each feature relative to entire image.**Aspect Ratio**: Ratio of the major and minor axis lengths of each feature.**Average Neighbor**: Each feature’s average distance to its neighbors, as defined by the features’ Delaunay triangulation. Triangulation and distance are both calculated from the features’ centroids.**Caliper Diameter**: Largest line length that fits across each feature. Equivalently, the distance between the two points in the feature farthest from each other, including those points.**Convex Area:**Area of each feature’s tightest-fitting convex hull.**Eccentricity:**Describes how elongated or circular each feature is. 0 is a perfect circle. 1 is a straight line.**Equivalent Diameter:**Diameter of each feature if each was a circle of the same area.**Feature Number:**Numbers that are assigned to features when measurements are generated.**Filled Area:**Area of each feature with holes filled in.**Filled Area/Area:****First Moment of Inertia:**First moment of each feature. Describes how much feature area is extended away from its centroid.**First Moment of Inertia/Area:**Ratio between the first moment of each feature and its area.**Intensity Mean:***(requires Companion Image)*Grayscale intensity average of the entire Current Image.**Intensity StdDev:***(requires Companion Image)*Grayscale intensity standard deviation of the entire Current Image.**Intensity Sum:***(requires grayscale Companion Image)*Grayscale intensity sum over the entire Current Image.**Length – X:**Length of each feature’s bounding box in the X-direction.**Length – Y**: Length of each feature’s bounding box in the Y-direction.**Major Axis Length:**Major axis length of ellipse fit to each feature.**Minor Axis Length:**Minor axis length of ellipse fit to each feature.**Moment Invariant (Omega-1):**High-order moment which describes shape properties of each feature [1,2].**Moment Invariant (Omega-2):**High-order moment which describes shape properties of each feature [1,2].**Moment Invariant (Phi-1):**High-order moment which describes shape properties of each feature [1,2].**Moment Invariant (Phi-2):**High-order moment which describes shape properties of each feature [1,2].**Nearest Neighbor**: Each feature’s distance to the closest other feature, calculated from the features’ centroids.**Number of Features:***(requires Companion Image)*Number of features in the companion image contained within the feature.**Number of Holes:**Number of holes contained within the feature.**Orientation:**Angle of the ellipse fit to each feature with respect to the positive X-axis. Positive angles are clockwise rotations and negative counterclockwise.**Perimeter:**Length of perimeter of each feature.**Perimeter/Area:**Perimeter of each feature relative to its area.**Roughness:**Ratio between the area of tightest-fitting convex hull and the area of each feature.**Roundness:**Ratio of equivalent diameter to caliper diameter (see above).

### 2. Features, Edge Features, Units

**Features**: You can choose which features you want to be rejected between white and black.**Edge Features**: You can choose to include or ignore edge features when choosing features to reject. You can also choose to only reject edge features.**Units**: The units you would like use to reject features.

### 3. Threshold Value

Select the threshold value (of the set measurement) for rejecting features and specify whether you would like to reject or keep features below the threshold value.

### 4. Proximity Awareness

Lets you consider the features above or below the threshold as *candidates* for removal, but only actually removed them if their neighbors pass the specified threshold.

**Less Than / =, Greater Than / =:**Choose whether neighboring features must be less than or equal to, or greater than or equal to, in order to pass the threshold.**None:**Do not use neighborhood conditionals**Within Distance**: Consider features whose centroids are within certain distance. Enter distance in which to search (in pixels);

-**Number:**Consider number of features. Enter critical number of features.

-**Total Area:**Consider total area of features. Enter critical total area (in pixels).

-**Average Area:**Consider average area of features. Enter critical average area (pixels).**Local Window**: Consider local window about each feature, including partial neighboring features.

-**Number:**Consider number of features. Enter critical number of features.

-**Total Area:**Consider total area of features. Enter critical total area (in pixels).

-**Average Area:**Consider average area of features. Enter critical average area (pixels).

## References

[1] Rosin, Paul L. 2003. “Measuring Shape: Ellipticity, Rectangularity, and Triangularity.” Machine Vision and Applications 14 (3): 172–184.

[2] MacSleyne, J P, J P Simmons, and M De Graef. 2008. “On the Use of Moment Invariants for the Automated Analysis of 3D Particle Shapes.” Modelling and Simulation in Materials Science and Engineering 16 (4) (June 1): 045008.

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