Selecting a Search Accuracy
When you perform a search using CNLSearch, you can specify the relative accuracy level for the search. CNLSearch supports coarse, fine, and veryfine searches. The search methods produce increasingly accurate results at the cost of requiring additional memory and time. In addition, the more accurate search methods provide for better discrimination in confusing images. To optimize the performance and space requirements of your application, you should specify the coarsest search method that provides the accuracy and discrimination that your application requires.
The table below lists the accuracy of the different search methods for each of the supported CNLSearch algorithms.
|
|
Accuracy |
||
|
Algorithm |
Coarse |
Fine |
Veryfine |
|
CnlpasLinear |
± 2 pixels |
± 1 pixel |
± 0.25 pixel |
|
Search |
± 2 pixels |
± 1 pixel |
± 0.25 pixel |
|
CnlpasNonlinear |
± 2 pixels |
± 1 pixel |
± 0.5 pixel |
The search accuracies listed in the table above represent the best accuracy that CNLSearch can achieve. Depending on the particular image being searched, the actual accuracy may be less than that listed in the table above.
The tables below indicate the relative speed difference for using the different search methods with each of the CNLSearch algorithms.
|
|
Accuracy |
||
|
Algorithm |
Coarse |
Fine |
Veryfine |
|
CnlpasLinear |
100% |
110% |
120% |
|
Search |
100% |
110% |
120% |
|
CnlpasNonlinear |
100% |
150% |
200% |
Relative search times, score greater than confusion threshold
|
|
Accuracy |
||
|
Algorithm |
Coarse |
Fine |
Veryfine |
|
CnlpasLinear |
100% |
150% |
200% |
|
Search |
100% |
150% |
200% |
|
CnlpasNonlinear |
100% |
200% |
300% |
Relative search times, score less than confusion threshold