Measuring memetic algorithm performance on image fingerprints dataset

Abstract

Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is matching input fingerprint with data that saved in the database. In this paper, we measure the performance of the memetic algorithm to process the image fingerprints dataset. Before we run this algorithm, we divide our fingerprints into four groups according to its characteristics and make 15 specimens of data, do four partial tests and at the last of work we measure all computation time.

Sunfa Ata Zuyan machine learning models for moon phase detection: algorithm, prototype and performance comparison

“…Afterwards, using the density-based spatial clustering of applications with noise (DBSCAN), the existing elements in the picture are classified, and the biggest one with the round outline is chosen as the target. In the end, the part of the image matrix which includes the target is added [21], [22]. Erosion (minkowsky subtraction) works based on two processes of eliminating and shrinking boundary points and is mainly used for binary images but can also be applied to grayscale images [12], [19], [22], [23].…”

Reliability Comparison of High Performance Computing between Single Thread Loop and Multiple Thread Loop using Java-Based Programming at Fingerprint Data Processing

“…The testing process between Single Thread Loop and Multiple Thread Loop whose testing process uses the test logic architecture that has been illustrated in Figure 3, as well as the flow of the testing process which has also been illustrated in Figure 6. From the test results based on a predetermined scenario, it was found that the specimen number two shows the test results which are quite significantly high [14], In contrast specimen one shows the lowest test results in terms of access speed. Roughly speaking, these conditions show the weight and complexity level of the file to be one indicator of speed or slowness processing data from each of these specimens; it can be seen in the illustration of the comparison of results in figure 12 and also table of test results in table 3.…”

The influence of data size on a high-performance computing memetic algorithm in fingerprint dataset

“…To design a memetic algorithm, the considered problem is optimization as a specific problem [20]. Assiroj et al [21], use the original memetic algorithm to process the fingerprint dataset and this algorithm works properly. This algorithm is also could be parallelized, Mirsoleimani et al [22], implements parallel type on the graphics processing unit (GPU).…”