Dear researchers,
Recently, I have proposed a new model for pattern recognition.
Article A new model for pattern recognition ✩
The model is examined on the faces images to build a face recognition system. It deals with continuous and discrete values of the extracted features.
The continuous Farhan model (CFM) represents each block of features with its mean and variance, whereas the discrete Farhan model (DFM) uses the quantization method to implement each block with a single value. The quantization method is also explained in the following articles:
Conference Paper Using only two states of discrete HMM for high-speed face recognition
Conference Paper A novel face recognition method based on one state of discre...
The disadvantage of the quantization method is estimating the quantization levels and weights vectors that depend on the maximum and minimum values using a trial-and-error process. In the case of updating the database (add or remove an individual), the whole system is required to be retrained because the maximum and minimum values may be altered.
The question is:
How to assign a single value to each vector without using the quantization method. It is worth noting that each vector comprises only three elements; mean, maximum variance, and standard deviation.
Thank you in advance for your suggestions.
This would be a great question to post in our new free medical imaging question and answer forum ( www.imagingQA.com ), there a number of image analysis and machine learning experts in the community. If useful, please feel free to open a new topic at the link below :
https://community.imagingqa.com/c/questions/5
Dear James O'Callaghan
Thank you for your advice.
I will post the question in the suggested forum.
You can use mean or median. Or using vector. Or you can use feature selection algorithms for reduction.
Dear Bayan Alsaaidah
I have updated the question by adding more information.
Each block is implemented with three values; mean, maximum variance, and standard deviation. The goal is to merge these three values into a single value.
Thank you for your participation.
Dear Sir,
You can use different merge techniques for merging three individual values into a single value like, add operation, average operation, etc. There are many algorithms in machine learning for feature selection like SVM, PCA, etc. You can also explore those techniques.
Dear Deepali Verma
I have tried different methods, but the results were not satisfactory.
I am searching for the best method that can be applied to different databases.
Thank you for your suggestion.
Dear Janusz Bobulski
Thank you for your suggestion.
Please explain what do you mean by ((add two elements equal 0)).
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