# FindBlobs

FindBlobs is used to filter and score blobs in a Blobs structure by a weighted set of ideal values.

## FindBlobs Overview

Using the FindBlobs parameter settings, a formula is created that calculates a score to measure how closely the blobs referenced in the Blobs data structure match an "ideal" blob A blob is a group of pixels on the image that form a distinct pattern, typically used to represent objects, features, or areas of interest in object detection and segmentation tasks.. Based upon the parameter settings, FindBlobs returns only those blobs that match the specified requirements.

Each blob in the referenced Blobs data structure undergoes a two-step process of analysis. First, each of the individual FindBlobs parameter settings creates a formula that evaluates that particular parameter value. For instance, the Angle score would be computed by dividing the differences of the Range and the Angle value of the Angle parameter and the Range and the Angle value of the referenced blob, multiplied by the Weight value. After the individual scores have been computed, each of the individual parameter scores are added together and divided by the sum of the individual Weight parameter values. This score is then compared against the Accept Thresh value to determine whether or not the blob meets the specified requirements.

Once FindBlobs has filtered and sorted the extracted blobs, a new Blobs data structure and accompanying result table is automatically inserted into the spreadsheet. The result table is sorted by how closely the found blobs match the configured requirements, in descending order.

FindBlobs can be extremely useful in classifying features for defect detection. For example, if the job A job is a user-configured program in In-Sight Spreadsheet consisting of functions and designed for specific applications. You can create and edit jobs using the In-Sight Spreadsheet interface, and load them on a vision system for deployment in a live environment. were to detect scratches on a surface, FindBlobs could be configured to return only those blobs with higher Elongation values. Or, if the goal was to detect jagged edge defects, FindBlobs could be configured to return only those blobs with higher Perimeter or Spread values.

Inputs

Parameter | Description
Blobs | This parameter uses Cell References to a Blobs data structure that is to be filtered and sorted.
Number to Find | This parameter specifies the maximum number (1 to 4 096; default = 3) of blobs to return. If there are more blobs in the image whose scores exceed the Accept Thresh setting, the blobs with the highest scores will be selected. Note: If the value of the Number to Find parameter is greater than zero, FindBlobs will automatically insert a result table containing a maximum of 10 entries that correspond to the first 10 blobs in the Blobs data structure. If you wish to display more entries, you can expand the table by copying the last row and pasting additional rows at the end; make sure to increment the index number of any newly-pasted row so that the proper blob is indexed.
Accept Thresh | Specifies the minimum acceptable match score (0 to 100; default = 10). FindBlobs will return only those blobs with match scores exceeding the Accept Thresh. The match score is computed with the following formula: (Angle score + Area score + Elongation score + Holes score + Perimeter score + Spread score) * (100/Sum of the parameters' Weight values)
Angle | This parameter is used to configure the scoring formula that identifies the ideal Angle score (+/- CCW degrees) of found blobs. Angle Scoring Formula The FindBlobs Angle score is computed by using the following formula: Angle Score = [(Range + Angle) - BlobAngleVal]/Range * WeightVal BlobAngleVal = the referenced blob's output Angle value WeightVal = Weight/(sum of all weight values) * 100
Angle | The ideal blob angle (-360 to 360; default = 0).
Range | The blob angle tolerance, in similarity scoring (0 to 360; default = 0).
Weight | The relative importance of blob angle, in similarity scoring (0 to 100; default = 0).
Area | This parameter is used to configure the scoring formula that identifies the ideal Area score of found blobs. Area Scoring Formula The FindBlobs Area score is computed by using the following formulas, depending on the BlobAreaVal and the Area value: If the BlobAreaVal is greater than the Area value, this formula is used: Area Score = [(Range + Area) - BlobAreaVal]/Range * WeightVal If the BlobAreaVal is less than the Area value, this formula is used: Area Score = [BlobAreaVal - (Area - Range)]/Range * Weight Val BlobAreaVal = the referenced blob's output Area value WeightVal = Weight/(sum of all weight values) * 100
Area | The ideal blob area size, in pixels (0 to 100 000 000; default = 1 000).
Range | The blob area tolerance, in similarity scoring (0 to 100 000 000; default = 20 000).
Weight | The relative importance of blob area, in similarity scoring (0 to 100; default = 50).
Elongation | This parameter is used to configure the scoring formula that identifies the ideal Elongation score of found blobs. Elongation Scoring Formula The FindBlobs Elongation score is computed by using the following formula: Elongation Score = [(Range + Elongation) - BlobElongationVal]/Range * WeightVal BlobElongationVal = the referenced blob's output Elongation value WeightVal = Weight/(sum of all weight values) * 100
Elongation | The ideal blob elongation (0 to 900 000; default = 1).
Range | The blob elongation tolerance, in similarity scoring (0 to 900 000; default = 2).
Weight | The relative importance of blob elongation, in similarity scoring (0 to 100; default = 50).
Holes | This parameter is used to configure the scoring formula that identifies the ideal Holes score of found blobs. Holes Scoring Formula The FindBlobs Holes score is computed by using the following formula: Holes Score = [(Range + Number) - BlobHolesVal]/Range * Weight Val BlobHolesVal = the referenced blob's output Holes value WeightVal = Weight/(sum of all weight values) * 100
Number | The ideal blob hole count (0 to 10 000; default = 0).
Range | The blob hole count tolerance, in similarity scoring (0 to 10 000; default = 2).
Weight | The relative importance of blob hole count, in similarity scoring (0 to 100; default = 0).
Perimeter | This parameter is used to configure the scoring formula that identifies the ideal Perimeter score of found blobs. Perimeter Scoring Formula The FindBlobs Perimeter score is computed by using the following formula: Perimeter Score = [(Range + Perimeter) - BlobPerimeterVal]/Range * WeightVal BlobPerimeterVal = the referenced blob's output Perimeter value WeightVal = Weight/(sum of all weight values) * 100
Perimeter | The ideal blob perimeter (0 to 100 000; default = 1 000).
Range | The blob perimeter tolerance, in similarity scoring (0 to 100 000; default = 10 000).
Weight | The relative importance of blob perimeter, in similarity scoring (0 to 100; default = 50).
Spread | This parameter is used to configure the scoring formula that identifies the ideal Spread score of found blobs. Spread Scoring Formula The FindBlobs Spread score is computed by using the following formula: Spread Score = [(Range + Spread) - BlobSpreadVal]/Range * WeightVal BlobSpreadVal = the referenced blob's output Spread value WeightVal = Weight/(sum of all weight values) * 100
Spread | The ideal blob spread (0 to 900 000; default = 1).
Range | The blob spread tolerance, in similarity scoring (0 to 900 000; default = 2).
Weight | The relative importance of blob spread, in similarity scoring (0 to 100; default = 50).
Show | Specifies the display mode for FindBlobs graphical overlays on top of the image.
0 = hide all (default) | All graphics will be hidden, except when the cell containing the FindBlobs function Functions are tools that are available in Spreadsheet for processing and analyzing acquisitions or other results. You can add functions to your Spreadsheet job to create tool chains and produce results for specific applications. is highlighted in the spreadsheet.
1 = result graphics only | Blob outlines will be displayed at all times.

Outputs

Returns | A Blobs data structure containing the matching blobs sorted by score, or #ERR if any of the input parameters are invalid.
Results | When FindBlobs is initially inserted into a cell, a results table is created in the spreadsheet using the following Blobs Vision Data Access functions. Note: If the value of the Number to Find parameter is greater than zero, FindBlobs will automatically insert a result table containing a maximum of 10 entries that correspond to the first 10 blobs in the Blobs data structure. If you wish to display more entries, you can expand the table by copying the last row and pasting additional rows at the end. Make sure to increment the index number of any newly-pasted row so that the proper blob is indexed. Additional data elements can be accessed by using the Blobs Vision Data Access functions.
Label | Function Name | Description
Index |  | Index position of the blobs.
X | GetX(Blobs, Blob Index) | Returns the x-coordinate of the center of mass, or centroid, of a blob.
Y | GetY(Blobs, Blob Index) | Returns the y-coordinate of the center of mass, or centroid, of a blob.
Angle | GetAngle(Blobs, Blob Index) | Returns the angle of the principal, or major, axis of a blob with respect to the Y-axis.
Color | GetColor(Blobs, Blob Index) | Returns the color value of a blob: 0 = black 1 = white
Score | GetScore(Blobs, Blob Index) | A measure of how closely the blob matches the criteria of a FindBlobs function.
Area | GetArea(Blobs, Blob Index) | Returns the area of the blob, measured in pixels. Note: If the blob has holes, the Area value is different depending on whether you check the Fill Holes checkbox in the DetectBlobs function.
Elongation | GetElongation(Blobs, Blob Index) | Returns a value that represents how the pixels of a blob stretch out from the center of mass, or centroid. For example, a circle has an Elongation value close to zero, while a nail has a high Elongation value.
Holes | GetHoles(Blobs, Blob Index) | Returns the number of holes contained within the blob. Note: The function only returns holes whose area is greater than the Area Limit: Min value you give in the DetectBlobs function.
Perimeter | GetPerimeter(Blobs, Blob Index) | Returns the length of the boundary around the blob. The perimeter is calculated by counting the external edges of the pixels that form the boundary of the blob.
Spread | GetSpread(Blobs, Blob Index) | Returns a value that represents the distribution of pixels away from the center of mass, or centroid. For example, a circular shaped object has a lower Spread value than an oval shaped object.

See the Blobs Vision Data Access functions for details on the result table.