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Deep convolutional neutral networks have achieved great success on image recognition tasks. Yet, it is non-trivial to transfer the state-of-the-art image recognition networks to videos as per-frame evaluation is too slow and unaffordable. We present deep feature flow, a fast and accurate framework for video recognition. It runs the expensive convolutional sub-network only on sparse key frames and...
Segmentation of the optic nerve head or optic disc in digital retinal fundus photographs is a non-invasive procedure that plays an important role in early detection of abnormalities of the eyes, particularly glaucoma diseases. Developing an automatic system, we employ image processing techniques coupled with graph cut algorithms from combinatorial optimization. Avoiding the need of manual pre-segmentation...
There is a vital need to map seagrass ecosystems in order to determine worldwide abundance and distribution. Currently there is no established method for mapping the pothole or scars in seagrass. Detection of seagrass with optical remote sensing is challenged by the fact that light is attenuated as it passes through the water column and reflects back from the benthos. Optical remote sensing of seagrass...
We propose a novel method for video object proposal to generate sequences of bounding boxes for each object candidate in videos, namely object trajectory proposals. Unlike the image-based methods that produce object proposals independently in each video frame, our method generates temporally consistent proposals in the form of object trajectories, which is crucial for subsequent analysis of object...
Diabetic Retinopathy and Diabetic Macular Edema are diseases that affect vision and eventually may lead to blindness. Early detection is a must to prevent the progression of the disease imploring the need for effective computer-aided diagnostic techniques. In the following research paper, a robust method has been proposed to segment hard exudates from digital, color fundus images using anisotropic...
A binarization algorithm based on strokes edge detection is presented which could binary the images of palm leaf manuscripts effectively with pretty performance in this paper. Firstly, the binarized contrast map is obtained by using an adaptive algorithm. Secondly, the stroke edge map is detected by combining the binarized contrast map with Canny edge map based on the bitwise AND operator. And then,...
In this paper, we propose a novel unsupervised optical remote sensing change detection (CD) based on pre-trained convolutional neural network (CNN) on ImageNet dataset and superpixel (SLIC) segmentation technique. The proposed approach can be divided into three steps. First, bi-temporal images are stacked, and Principal Component Analysis (PCA) is applied to extract three higher uncorrelated channels,...
A video segmentation method based on strong target constrained video saliency (STCVS) is proposed in this paper. In order to detect the salient region fast and effectively, the proposed STCVS is extracted based on the extension of image saliency by enforcing the salient region constrained with the location, scale and color model of the target. Besides, according to the results of STCVS, the super-pixel...
Image processing is an inevitable tool for visual tracking. Visual object tracking is a very hot area of research in the computer vision. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and in general, deal with the extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the...
Accurate localization and segmentation of an optic disk (OD) is an important problem in the analysis of abnormality conditions such as optic disk shrinking/swelling, pale optic disk and glucoma. Hence, this paper proposes an automated fast and accurate OD localization and segmentation technique. In this work, OD localization is performed using the extended feature projection method (EFP) based on...
In recent years, breast cancers have been diagnosed by several imaging modalities. One of these imaging methods is the diffuse optical tomography (DOT) system. In the presented study, in-vitro data were acquired from a breast phantom using the our designed DOT system. Breast phantoms were reconstructed in three dimensions (3D) using Truncated Conjugate Gradient (TCG) reconstruction algorithm. Then,...
The fovea is one of the most important anatomical landmarks in the eye and its localization is required in automated analysis of retinal diseases due to its role in sharp central vision. In this paper, we propose a two-stage deep learning framework for accurate segmentation of the fovea in retinal colour fundus images. In the first stage, coarse segmentation is performed to localize the fovea in the...
Accurate visualization of retinal vasculature is essential for the diagnosis of the severity of various vascular diseases. Therefore blood vessel segmentation becomes an indispensable part of computer-based retinal image analysis systems. Retinal fundus images of premature infants are of relatively low contrast, and hence difficult to segment, when compared to adult retina images. An efficient segmentation...
For the screening of any eye disease, the detection of Optic disc is a crucial step. In this paper, a novel and robust technique is proposed to detect the Optic nerve head (ONH) in the fundus image automatically. The proposed algorithm uses the directional characteristics of vessel structure and a set of characteristics of optic nerve head as the key factors for the detection. The ideas behind the...
Focusing on the automatic image registration problem of SAR and optical image because of the inconsistency of radiometric and geometric properties, a new algorithm based on line features and spectral graph matching is presented in this paper. Firstly, different edge detectors are employed to detect the line segments in both optical and SAR images respectively. With the random sampling consensus method,...
Conventional approaches to image de-fencing have limited themselves to using only image data in adjacent frames of the captured video of an approximately static scene. In this work, we present a method to harness disparity using a stereo pair of fenced images in order to detect fence pixels. Tourists and amateur photographers commonly carry smartphones/phablets which can be used to capture a short...
Retinal image inspection is crucial to identify and supervise a class of retinal diseases. Image processing procedures are widely considered to extract the infected region of retinal image in order to have a clear idea about the disease. In this paper, heuristic algorithm assisted multi-level thresholding and level set approaches are considered to extract the optic disc from the retinal image dataset...
The traditional method of tea leaves harvesting is done in following ways, such as Hand Plucking using knife, Hand Plucking without using Knife. In the recent years the harvesting machines are introduced which can be operated by a single person or multiple persons and also a robotic vehicle. The challenges faced in the above systems are not enough capacity of human resources, intruding of wild animals...
In this paper, we propose a novel moving-objects detection method which, in contrast to state-of-the-art moving-objects detection methods, takes static feature points into consideration during detection. It benefits both the tracking and mapping approaches in real-time Simultaneous Localization and Mapping (SLAM) system whose localization depends on static objects primarily. Our method obtains accurate...
Detection of vehicles in remote sensing data represents a captivating and challenging task that has been studied during many years. The state-of-the-art detection tools can be subdivided into implicit and explicit methods; the latter ones provide detection results by means of some explicitly characterizing features. Mostly, these methods rely on optical aerial images in which vehicles appear distorted...
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