“Bag of keypoints”-based biomedical image search with affine covariant region detection and correlation-enhanced similarity matching

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.Â Â Keywords: RGB, HSL, image searchingÂ Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%.Â Kata Kunci: RGB, HSL, pencarian gambar

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Tag Based Image Search Using User Re-ranking

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i7.772775 ◽

2018 ◽

Vol 6 (7) ◽

pp. 772-775

Author(s):

S. N. Paraj

Keyword(s):

Image Search

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INTRODUCING TENSOR ANALYSIS FOR BIOMEDICAL IMAGE REGISTRATION

10.26678/abcm.enebi2018.eeb18-0110 ◽

2018 ◽

Cited By ~ 1

Author(s):

Wilian Fiirst ◽

José Montero ◽

ROGER RESMINI ◽

Anselmo Antunes Montenegro ◽

Trueman McHenry ◽

...

Keyword(s):

Image Registration ◽

Tensor Analysis ◽

Biomedical Image ◽

Biomedical Image Registration

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Improving the Computational Cost for Copied Region Detection in Forensic Images

Journal of Science and Technology Issue on Information and Communications Technology ◽

10.31130/jst.2016.28 ◽

2016 ◽

Vol 2 (1) ◽

pp. 55

Author(s):

Tu Huynh-Kha ◽

Thuong Le-Tien ◽

Synh Ha ◽

Khoa Huynh-Van

Keyword(s):

Wavelet Transform ◽

Euclidean Distance ◽

Research Work ◽

Computational Cost ◽

Correlation Coefficients ◽

Zernike Moments ◽

Computational Time ◽

Discrete Wavelet ◽

Feature Vectors ◽

Region Detection

This research work develops a new method to detect the forgery in image by combining the Wavelet transform and modified Zernike Moments (MZMs) in which the features are defined from more pixels than in traditional Zernike Moments. The tested image is firstly converted to grayscale and applied one level Discrete Wavelet Transform (DWT) to reduce the size of image by a half in both sides. The approximation sub-band (LL), which is used for processing, is then divided into overlapping blocks and modified Zernike moments are calculated in each block as feature vectors. More pixels are considered, more sufficient features are extracted. Lexicographical sorting and correlation coefficients computation on feature vectors are next steps to find the similar blocks. The purpose of applying DWT to reduce the dimension of the image before using Zernike moments with updated coefficients is to improve the computational time and increase exactness in detection. Copied or duplicated parts will be detected as traces of copy-move forgery manipulation based on a threshold of correlation coefficients and confirmed exactly from the constraint of Euclidean distance. Comparisons results between proposed method and related ones prove the feasibility and efficiency of the proposed algorithm.

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