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The main contribution of this work lies in the context of the quality assessment of spectral image processing operators or algorithms. Several means to define quality measurements for low-level spectral image processing tools are explored, i.e. Spectral distance and spectral image filtering. The quality assessment starts from simple theoretical validation on simulated spectra to reduced and full reference...
An approach is suggested for automating fish identification and measurement using stereo Baited Remote Underwater Video footage. Simple methods for identifying fish are not sufficient for measurement, since the snout and tail points must be found, and the stereo data should be incorporated to find a true measurement. We present a modular framework that ties together various approaches in order to...
This paper proposes an edge detection technique based on the Multiscale Product of Riesz Wavelet Transform for color image. The product of the wavelet transform combines the advantages of the used scales: in large scale it is strongly anti-noise, and in small scale it can accurately locate edge. The Riesz wavelet transform is a complex wavelet transform (WT) which comes to overcome the discrete wavelet...
Depth maps generated by Kinect cameras often contain a significant amount of missing pixels and strong noise, limiting their usability in many computer vision applications. In this paper we present an efficient hole filling and damaged region restoration method that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach based on a modified exemplar-based...
Edge detection is one of the most commonly used operations in the field of image processing. The traditional Canny edge detector is widely used in gray-scale image processing. However, this traditional edge detector is unable to deal with color images efficiently. The problem arises due to the double threshold technique: hysteresis threshold. In this paper, we have developed a new double threshold...
In this paper, we propose a novel algorithm for colour iris segmentation. The algorithm may be divided into the following components: coarse iris localization, limbic boundary segmentation, pupillary boundary segmentation, eyelids fitting, reflection and shadow removal. The key contribution of the proposed algorithm is that we demonstrate the power of sparsity induced by ℓ1-norm in overcoming the...
Automatic recognition of handwritten texts in video lectures has important applications. In video lectures, the presenter usually writes on white / colored board. The video camera often captures the writing board along with certain other objects possibly including the presenter itself. Recognition of handwritten texts from such a video frame requires prior detection of the region of texts in the frame...
In this paper, we present a non-invasive method of counting fish in their natural habitat using automated analysis of video data. Our approach uses three modular components to preprocess, detect, and track the fish. The preprocessing reduces noise present in the image while enhancing the fish using several different techniques. The fish detection is based on two background subtraction algorithms which...
Noise is inherent in digital systems. To smooth a point cloud while preserving sharp edges, a new 3D bilateral filter is proposed. It uses the point cloud normal vector in addition to color as a position vector for preserving sharp edges while smoothing the color. The bilateral blurs data while preserving strong edges. In 2D images, the concept of edge is defined by an abrupt change in color. In this...
In this paper, we present a scalable arrow detection technique for biomedical images to support information retrieval systems under the purview of content-based image retrieval (CBIR) and text information retrieval (TIR). The idea primarily follows the criteria based on the geometric properties of the arrow, where we introduce signatures from key points associated with it. To handle this, images are...
This work tackles the challenging problem of multi-shot person re-identification in realistic unconstrained scenarios. While most previous research within re-identification field is based on single-shot mode due to the constraint of scales of conventional datasets, multi-shot case provides a more natural way for person recognition in surveillance systems. Multiple frames can be easily captured in...
Background subtraction is a popular technique used in accurate foreground extraction with a stationary background. Since most outdoor surveillance videos are taken in complex environments, their "stationary" backgrounds change in some unknown patterns, which make the perfect foreground extraction very difficult. Based on visual background extractor (ViBe) scheme, in this paper we propose...
Huge variety of medicine cures diseases. But unlabeled pills sometimes confuse people, even causing adverse drug events. This paper introduces a high accuracy automatic pill recognition method based on pill imprint which is a main discriminative factor between different pills. To describe the imprint information clearly, we propose a Two-step Sampling Distance Sets (TSDS) descriptor based on Distance...
It is common for CCTV operators to overlook interesting events taking place within the crowd due to large number of people in the crowded scene (i.e. marathon, rally). Thus, there is a dire need to automate the detection of salient crowd regions acquiring immediate attention for a more effective and proactive surveillance. This paper proposes a novel framework to identify and localize salient regions...
Video tools developed today, teachers can record lecture videos and upload these lecture videos to e-learning system themselves. However, some students may only do not understand some fragments but they have to waste unnecessary time download entire video, and therefore video scene segmentation is relative importance. In addition, in traditional teaching model, students must listen and transcribe...
In this paper, we present a depth super-resolution framework by fusing depth imaging and stereo vision for high-resolution and high-accuracy depth maps. Depth cameras and stereo vision have their own limitations in some aspects, but their characteristics of range sensing are complementary. Thus, combining both approaches can produce more satisfactory results than either one. Unlike previous fusion...
Automatic Image annotation is an important open problem in computer vision. In real world dataset environment, image labels are often noisy. For the task of image annotation with weakly labels, we propose SNLWL, a semantic neighborhood learning model from weakly labeled dataset. Missing labels are replenished using reweighting the error loss function. Then semantic balanced neighborhood is construct...
The presence of large number of spectral bands in the remote sensing images results in difficulty of identifying various land cover regions. Land cover classification is one of the recent researches which find more application in satellite image processing. It is important to recognize different land classes from a multispectral satellite image as the raw image contains noises and less clarity. The...
License plate recognition (LPR) plays a major role in this busy world, as the number of vehicles increases day by day, theft of vehicles, breaking traffic rules, entering restricted area are also increases linearly, so to block this act license plate recognition system is designed. License Plate Recognition systems basically consist of 3 main processing steps such as: Detection of number plate, Segmentation...
Photographs are used to represent real-world events. Today many powerful image editing software's like Gimp, Photoshop etc. are available. Any kind of images can be manipulated by using these software's. Image composition or splicing is one of the important image manipulation technique. Sometimes these manipulated images are provided as evidence in court and this may cause serious problems. So it...
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