Contrast Enhancement by Top-Hat and Bottom-Hat Transform with Optimal Structuring Element: Application to Retinal Vessel Segmentation

Kushol, Rafsanjany; Kabir, Md. Hasanul; Salekin, Sirajus; Rahman, Asif

doi:10.1007/978-3-319-59876-5_59

Cited by 27 publications

(17 citation statements)

References 18 publications

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“…Transfromasi Bottom Hat digunakan untuk menghilangkan objek gelap dengan background terang. Persamaan dari transformasi ini dapat dilihat pada persamaan (5) berikuti [17]:…”

Section: B Pre-processingunclassified

Variasi Thresholding untuk Segmentasi Pembuluh Darah Citra Retina

Desiani

Zayanti

Primartha

et al. 2021

JEPIN

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Segmentasi pembuluh darah pada retina diperlukan pada deteksi dini penyakit Diabetic Retinopathy pada citra retina. Penelitian ini menggunakan tiga tahapan yaitu pre-processing, segmentasi dan post-processing yang akan membandingkan hasil dari 3 metode segmentasi yang menggunakan nilai Thresholding yaitu Adaptive Thresholding, Binary Thresholding, dan Otsu Thresholding. Hasil pengujian terhadap tiga metode yang digunakan menunjukan bahwa metode Binary Thresholding mendapat rata-rata akurasi, sensitivitas dan spesifisitas tertinggi yaitu 95%, 58%, 98%. Untuk Adaptive Thresholding mendapat rata-rata akurasi sebesar 91%, sensitivitas 36%, spesititiftas 97%. Dan metode Otsu Thresholding mendapatkan rata-rata akurasi 86%, sensitivitas 22%, dan spesifisitas 90%. Dari hasil ketiga metode ini dapat dilihat akurasi yang dihasilkan oleh metode Thresholding sudah sangat baik dalam melakukan segmentasi citra, tetapi nilai sensitivitas dari masing-masing metode Thresholding masih rendah. Hal ini dapat disimpulkan metode Thresholding masih sulit mendapatkan lebih banyak fitur pembuluh darah pada citra retina.

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“…Transfromasi Bottom Hat digunakan untuk menghilangkan objek gelap dengan background terang. Persamaan dari transformasi ini dapat dilihat pada persamaan (5) berikuti [17]:…”

Section: B Pre-processingunclassified

Variasi Thresholding untuk Segmentasi Pembuluh Darah Citra Retina

Desiani

Zayanti

Primartha

et al. 2021

JEPIN

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“…The excited colour video frames are transformed into greyscale and every tenth frame is processed. Top‐hat filtering [35] is applied for illumination adjustment that performs morphological opening with a structuring element SE of size α followed by the difference operation expressed as follows:

I_{o 1}^{false(i false)} false(x, y false) = I^{false(i false)} false(x, y false) \circ SE

I_{ad j}^{false(i false)} false(x, y false) = I^{false(i false)} false(x, y false) - I_{open}^{false(i false)} false(x, y false)

where

I_{o 1}^{false(i false)} false(x, y false)

and

I_{ad j}^{false(i false)} false(x, y false)

represent the morphed, and illumination adjusted frames, respectively. Whereas,

\circ

is the opening operator.…”

Section: Proposed Frameworkmentioning

confidence: 99%

Multimodal framework based on audio‐visual features for summarisation of cricket videos

Javed

Irtaza

Malik

et al. 2019

IET Image Processing

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“…To diminish the noise in the image we at first convert the input image into grayscale then apply fuzzy filter noise reduction method [10]. Another image enhancement and noise reduction method introduced in Kushol et al [11] for medical images is also tested but the result obtained after performing fuzzy filter proves better and one sample output is shown in Fig. 4.…”

Section: B Noise Reductionmentioning

confidence: 99%

An Android-Based Useful Text Extraction Framework Using Image and Natural Language Processing

Kushol¹,

Ahsan²,

Raihan³

2018

IJCTE

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With the rapid advancement of the mobile technologies, we now use mobile applications in every aspect of our life. At present when we find some useful information from business cards, newspapers, books, flyers and so on we do not usually note them rather we capture the image using mobile devices. However, the texts obtained from these images need to be processed further to make our task unequivocal. In this paper, we present an android application framework that can process the texts obtained from an image to get contact information from business cards as well as event information from magazines, posters or flyers. Google Cloud Vision API is used to retrieve the text from the captured image and OpenNLP to extract useful information from the obtained text. The experimental results show that our application is effective and efficient in terms of accuracy as well as processing time.

show abstract

Contrast Enhancement by Top-Hat and Bottom-Hat Transform with Optimal Structuring Element: Application to Retinal Vessel Segmentation

Cited by 27 publications

References 18 publications

Variasi Thresholding untuk Segmentasi Pembuluh Darah Citra Retina

Variasi Thresholding untuk Segmentasi Pembuluh Darah Citra Retina

Multimodal framework based on audio‐visual features for summarisation of cricket videos

An Android-Based Useful Text Extraction Framework Using Image and Natural Language Processing

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