An Enhanced Approach to Memetic Algorithm Used for Character Recognition

Welekar, Rashmi; Thakur, Nileshsingh V.

doi:10.1007/978-981-13-0617-4_57

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…Specifically, the use of algorithms for image processing has been done by [27], they have used memetic algorithm for image brightness enhancement; [28] use this algorithm to detect face emotion, while [29] use this algorithm for letter recognition. Handwritten recognition conducted by [30] and [31], retina recognition by [32], sub-pixel mapping imagery by [33], image classification by [34], and fingerprint matching with the memetic algorithm by [35], [36] and [5].…”

Section: Research Methods 21 Memetic Algorithmmentioning

confidence: 99%

Measuring memetic algorithm performance on image fingerprints dataset

Assiroj¹,

Warnars²,

Abdurrachman³

et al. 2021

TELKOMNIKA

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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.

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Section: Research Methods 21 Memetic Algorithmmentioning

confidence: 99%

Measuring memetic algorithm performance on image fingerprints dataset

Assiroj¹,

Warnars²,

Abdurrachman³

et al. 2021

TELKOMNIKA

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“…[14] conducts research to identify fingerprints in the big data framework with a distributed model. [15] states that a memetic algorithm can improve efficiency, reduce memory consumption, and has a better ability to utilize the resource system. In the research [16], the memetic [17], explained that a memetic algorithm can outperform the proposed method even this algorithm needs more computation time and also generates a high-quality solution.…”

Section: Reslated Researchmentioning

confidence: 99%

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

et al. 2021

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The fingerprint is one kind of biometric. This biometric unique data have to be processed well and secure. The problem gets more complicated as data grows. This work is conducted to process image fingerprint data with a memetic algorithm, a simple and reliable algorithm. In order to achieve the best result, we run this algorithm in a parallel environment by utilizing a multi-thread feature of the processor. We propose a high-performance computing memetic algorithm (HPCMA) to process a 7200 image fingerprint dataset which is divided into fifteen specimens based on its characteristics based on the image specification to get the detail of each image. A combination of each specimen generates a new data variation. This algorithm runs in two different operating systems, Windows 7 and Windows 10 then we measure the influence of data size on processing time, speed up, and efficiency of HPCMA with simple linear regression. The result shows data size is very influencing to processing time more than 90%, to speed up more than 30%, and to efficiency more than 19%.

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