Image Processing

The target scene consists of a black card with six cocoa beans of three different fermentation levels (High, correct, and low fermentation), two beans for each class, whose false-color composite is shown in the provided Figure (a), ground-truth map is shown in Fig. (b), and Fig. (c) presents its representative spectral signatures. The spectral image was acquired by the AVT Stingray F-080B camera by acquiring one band each time from  350 - 950 nm. The acquired image has a spatial resolution of 1096x712 pixels and 300 spectral bands of 2 nm width.

 

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This data set is regarding the paper submitted to the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications. The title of the paper is 'Molecular Signal Tracking and Detection Methods in Fluid Dynamic Channels' with the ID of TMBMC-TPS-19-0014.R2. The data are images taken from the particle image velocimetry (PIV) method and the Planar Laser-Induced fluorescence (PLIF) method. The images are being used to describe these two experimental methods for the molecular communication community.

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Dataset for Telugu Handwritten Gunintam

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Addtional datasets for the jounal paper subimitted to IEEE Transactions on Computational Imaging, including self-captured light field microscopy datasets with lab-assembled LF microscope.

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The color fractal images with independent RGB color components were generated using the midpoint displacement alogrithm, applied independenlty on each RGB color component. This data set contains 9 images of varying complexity, expressed as the color fractal dimension, as a function of the Hurst coefficient that was varied from 0.1 to 0.9 in steps of 0.1. Each fractal object was independently rendered as a color image. The data set is intented to be used as a reference data set for color texture complexity analysis when considering fractal dimension estimation. 

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The orchid flower dataset was selected from the northern part of Thailand. The dataset contains Thai native orchid flowers, and each class contains at least 20 samples. The orchid dataset including 52 species and the visual characteristics of the flower are varying in terms of shape, color, texture, size, and the other parts of the orchid plant like a leaf, inflorescence, roots, and surroundings. All images are taken from many devices such as a digital camera, a mobile phone, and other equipment. The orchids dataset contains 3,559 images from 52 categories.

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This is a dataset consisting of 8 features extracted from 70,000 monochromatic still images adapted from the Genome Project Standford's database, that are labeled in two classes: LSB steganography (1) and without LSB Steganography (0). These features are Kurtosis, Skewness, Standard Deviation, Range, Median, Geometric Mean, Hjorth Mobility, and Hjorth Complexity, all extracted from the histograms of the still images, including random spatial transformations. The steganographic function embeds five types of payloads, from 0.1 to 0.5.

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Accurate segmentation of test line and control line for colloidal gold immunochromatographic strip (GICS) images with image processing algorithms is essential to quantitative analysis of GICS. As common methods for GICS image segmentation, fuzzy c-means (FCM) algorithm and cellular neural network (CNN) algorithm both require presetting initial conditions (specifying initial parameters or training models) and take long running time, due to high calculation cost.

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This dataset contains the comparison results on the 'Euroc' public dataset of DVIO, VINS-Mono, and ROVIO.

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Smartphone has been one of the most popular digital devices in the past decades, with more than 300 million smartphones sold every quarter in the world wide. Most of the smartphone vendors, such as Apple, Huawei, Samsung, launch their new flagship smartphones every year. People use smartphone cameras to shoot selfie photos, film scenery or events, and record videos of family and friends. The specifications of smartphone camera and the quality of taken pictures are major criteria for consumer to select and buy smartphones.

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