scholarly journals Best Regression for Eye Recognition

2021 ◽  
pp. 4588-4596
Author(s):  
Ehsan M. Al-Bayati ◽  
Zaid F. Makki ◽  
Fadia W. Al-Azawi
Keyword(s):  
Great Proportion ◽  
Histogram Equalization ◽  
Biometric Recognition ◽  
Degree Polynomial ◽  
Adaptive Histogram Equalization ◽  
Straight Line ◽  
Surface Plot ◽  
Different Types ◽  
Eye Recognition ◽  
Different Characteristics

     Human eye offers a number of opportunities for biometric recognition. The essential parts of the eye like cornea, iris, veins and retina can determine different characteristics. Systems using eyes’ features are widely deployed for identification in government requirement levels and laws; but also beginning to have more space in portable validation world. The first image was prepared to be used and monitored using CLAHE which means (Contrast Limited Adaptive Histogram Equalization) to improve the contrast of the image, after that the 3D surface plot was created for this image then different types of regression were used and the better one was chosen. The results showed that power regression is better, and fitter than other fitting methods (8th, 7th, 6th, 5th, 4th, 3rd, 2nd) degree polynomial, and straight line respectively, when depending on the sum of residual squared. The estimations of R-square demonstrated that (5th, 6th, 7th, 8th) have a great proportion of variance in the model followed by (power, 4th, 3rd, 2nd, straight line) respectively. The conclusion from these results is that the power regression has a better fitting than other types of fitting functions for this study and similar ones.

PENERAPAN METODE CLAHE UNTUK MEMPERJELAS OBJEK PANTULAN KACA PADA CITRA DIGITAL

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Sulharmi Irawan ◽  
Yasir Hasan ◽  
Kennedi Tampubolon
Keyword(s):  
Image Processing ◽  
Computer Graphics ◽  
Digital Image ◽  
Histogram Equalization ◽  
Image Objects ◽  
Adaptive Histogram Equalization ◽  
Image Displays ◽  
Reflection Image

Glass reflection image displays unclear or suboptimal visuals, such as overlapping images that blend with overlapping displays, so objects in images that have information and should be able to be processed for advanced research in the field of image processing or computer graphics do not give the impression so that research can be done. Improvement of overlapping images can be separated by displaying one of the image objects, the method that can be used is the Contras Limited Adaptive Histogram Equalization (CLAHE) method. CLAHE can improve the color and appearance of objects that are not clear on the image. Images that experience cases such as glass reflection images can be increased in contrast values to separate or accentuate one of the objects contained in the image using the Contrast Limited Adaptive Histogram Equalization (CLAHE) method.Keywords: Digital Image, Glass Reflection, Contrast, CLAHE, YIQ.

Adaptive histogram equalization and its variations

1987 ◽  
Vol 39 (3) ◽  
pp. 355-368 ◽  
Author(s):  
Stephen M. Pizer ◽  
E. Philip Amburn ◽  
John D. Austin ◽  
Robert Cromartie ◽  
Ari Geselowitz ◽  
...  
Keyword(s):  
Histogram Equalization ◽  
Adaptive Histogram Equalization

scholarly journals PENERAPAN RANDOM FOREST UNTUK PENGENALAN JENIS IKAN BERDASARKAN PERBAIKAN CITRA CLAHE DAN DARK CHANNEL PRIOR

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
R.A. Pramunendar ◽  
Dwi Puji Prabowo ◽  
F. Alzami ◽  
R.A. Megantara
Keyword(s):  
Random Forest ◽  
Histogram Equalization ◽  
Dark Channel Prior ◽  
Adaptive Histogram Equalization ◽  
Dark Channel

Ancaman terhadap kekayaan alam semakin terlihat, oleh karena itu upaya untuk melindungi populasi biota perairan sangat menantang bagi banyak negara. Upaya untuk mengatasi kerusakan terhadap populasi ikan asli telah dilakukan dengan mengurangi populasi ikan invasif melalui teknik penangkapan ikan tradisional. Namun, teknik penangkapan tersebut tidak hanya menangkap spesies ikan invasif tetapi juga spesies asli. Oleh karena itu, masih diperlukan proses manual untuk memilah hasil tangkapan sehingga menghabiskan energi dan waktu. Maka, perlu ditingkatkan kemampuan pengenalan ikan secara otomatis dengan bantuan computer. Telah ada penelitian sebelumnya untuk mengenali jenis-jenis ikan, namun tidak banyak yang mempertimbangkan adanya noice atau artefak-artefak yang timbul karena kondisi bawah air serta efek fitur-fitur ikan yang saling berkaitan. Oleh karena itu dalam penelitian ini, peneliti  ini mengusulkan untuk melakukan analisis dampak pre-processing dari kombinasi algoritma CLAHE dan DCP yang diterapkan dalam klasifikasi ikan dengan Random Forest. Pre-processing yang yang diberikan bertujuan untuk mengatasi artefak atau noice yang timbul pada citra bawah air dan mengatasi efek dari fitur-fitur keragaman jenis ikan. Sehingga diharapkan mampu menghasilkan klasifikasi yang lebih baik dari penelitian sebelumnya. Klasifikasi dengan menggunakan Random Forest (RF) dengan perbaikan citra Dark Channel Prior (DCP) dan Contract Limited Adaptive Histogram Equalization (CLAHE), terbukti memberikan nilai akurasi rata-rata yang cukup tinggi yakni sebesar 98.51%, presisi 78.91%, dan recall 36.71%.

scholarly journals PERBAIKAN KUALITAS CITRA MAPS MENGGUNAKAN METODE CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION (CLAHE)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Dian Lestari Nasution
Keyword(s):  
Graphic Design ◽  
Histogram Equalization ◽  
Good Image ◽  
Image Processing Techniques ◽  
Adaptive Histogram Equalization ◽  
Image Contrast Enhancement ◽  
Image Improvement ◽  
Processing Techniques ◽  
Graphics Processing ◽  
Contrast Image

Map images that are on Google Maps can also be screenshooted, when taking image maps / maps the image quality is not optimal, this is because the ability of the computer used to take the image does not support high graphics. This map image can be used as material for the purposes of work that uses images such as graphic design, namely printing.The ability of computers that do not support large graphics processing in getting a good image is not a major problem in image improvement. Because the image that is not maximized, its color elements can be manipulated with digital image processing techniques, one of the methods for manipulating elements of image colors is the CLAHE method. The CLAHE method is applied and calculates the pixel values that exist in each RGB layer. In the field of graphic design images that have less intensity can be improved by increasing contrast. Image contrast enhancement can be done by the CLAHE method.Keywords: Maps Imagery, Contrast, CLAHE

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