Solution

Answer Part a

The matching stage is more important than the feature extraction stage after all possible features are extracted. This is because the matching stage is where the system compares the extracted features to a database of known features in order to identify the individual.

Answer Part b

Matching is the process of comparing two sets of features to determine if they are the same. This can be done using a variety of methods, but the most common is to use a mathematical algorithm to compare the two sets of features and look for similarities.

Explanation:

Explanation Part a

The feature extraction stage is important in biometric recognition because it is where the system extracts unique characteristics from an individual's appearance. These characteristics can be used to identify the individual later on.
However, the matching stage is more important than the feature extraction stage after all possible features are extracted. This is because the matching stage is where the system compares the extracted features to a database of known features in order to identify the individual.
The matching stage is more important than the feature extraction stage because it is the stage that actually identifies the individual.
The feature extraction stage is important because it extracts the unique characteristics that will be used for identification, but the matching stage is the one that actually does the identification.
The matching stage is more important than the feature extraction stage because it is the stage that actually identifies the individual.
The feature extraction stage is important because it extracts the unique characteristics that will be used for identification, but the matching stage is the one that actually does the identification.
The matching stage is more important than the feature extraction stage after all possible features are extracted because it is where the system compares the extracted features to a database of known features in order to identify the individual.

Explanation Part b

There are a variety of methods that can be used for matching, but the most common is to use a mathematical algorithm. This algorithm is designed to compare the two sets of features and look for similarities.
The algorithm will then score the similarity between the two sets of features. The higher the score, the more likely it is that the two sets of features are the same.
There are a variety of different algorithms that can be used for matching. The most common is the Euclidean Distance algorithm. This algorithm calculates the distance between two points in space. The closer the two points are, the more similar they are.
Another common algorithm is the Mahalanobis Distance algorithm. This algorithm is used to calculate the distance between two points in space, but it takes into account the variance of the data. This is important because it means that the algorithm is less likely to be fooled by outliers.
Once the algorithm has been chosen, the next step is to implement it. This can be done using a variety of different programming languages. The most common languages are C++ and Java. However, there are a variety of other languages that can be used.
Once the algorithm has been implemented, the next step is to test it. This can be done using a variety of different methods.
The most common is to use a dataset that has been previously labeled. This dataset can be used to train the algorithm and then to test it.
Once the algorithm has been tested, the next step is to deploy it. This can be done using a variety of different methods.
The most common is to use a web server. This will allow the algorithm to be accessed by anyone with an internet connection.
The final step is to maintain the algorithm. This can be done by periodically retraining the algorithm and by testing it on new data.

Q1. There are two main functions in biometric recognition: Feature Extraction and Matching. Determine which stage is important after all possible features are extracted. Support your answer with an explanation. Explain the implementation process of matching function.

Public Answer

Q1. There are two main functions in biometric recognition: Feature Extraction and Matching.

Determine which stage is important after all possible features are extracted. Support your answer with an explanation.

Explain the implementation process of matching function.