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Underwater obstacle detection is essential for safe deployment of autonomous underwater vehicles (AUVs). In this paper, we make an attempt to explore one kind of underwater obstacle detection strategy with the help of the Relative Total Variation(RTV) and Joint Guided Filtering(JGF). We first introduce one kind of virtual retinex model. Then we utilize the Relative Total Variation to extract the essential...
In this work we discuss an efficient strategy for reducing the negative impact of non-uniform illumination to panoramic image quality by proposing an adaptive correction algorithm based on the improved Bilateral Gamma function. Firstly the illumination component is extracted by a fast image guided filter. Then an improved bilateral Gamma function fed by the distribution characteristics of illumination...
Welding is a process recognized by the laborious work and hazardous work environment it takes place, but it is an important process in different industrial scenarios, like the shipbuilding industry. The use of robots has been increasing in recent years, reducing the human interference necessary for the process. This paper proposes a system for automated seam tracking and a geometric welding bead analysis...
Multi-channel visual reality system based on PC cluster can give users strong sense of immersion. This paper discusses the synchronous problem in multi-channel visual reality system. For the viewpoint synchronization, this paper brings forward a message communication mechanism based on change of user operating status. This mechanism can reduce the message amount by a large margin, so the message block...
Computer Vision and Machine Learning are the key to develop autonomous robots. While engaged with a IEEE Open Challenge, in which the robots need to recognize a miniature of a cow, we saw a solution in these areas. The main contribution of this paper is the algorithm implemented to identify and follow a known object, the miniature of a cow. We are constructing an application based on Image Processing...
Karyotyping helps to evaluate the size, shape and number of chromosomes. It is a screening and diagnostic process for finding various abnormalities related with chromosomes. Banding pattern is unique for each pair of chromosome. In the present research, fractional derivatives find an important place in the field of signal processing and digital image processing. This paper proposes a method for segmenting...
Removing undesired reflections from a photo taken in front of a glass is of great importance for enhancing the efficiency of visual computing systems. Various approaches have been proposed and shown to be visually plausible on small datasets collected by their authors. A quantitative comparison of existing approaches using the same dataset has never been conducted due to the lack of suitable benchmark...
For 2D visual applications, using template matching algorithm to identify objects is difficult to get accurate matching results. Because the traditional template matching algorithm is based on gray-scale correlation, it is sensitive to rotation, illumination variation and noise. By improving the classical Canny operator, obtain the precise edge feature image. Employ the binarization to feature image...
As the human eye on the image of different regions of the contrast sensitivity is different, it is particularly important to segment the image region more accurately in the image quality evaluation. Based on this, this paper presents a non-reference image region division method based on deep learning. Firstly, the Canny operator performs image edge detection at low threshold to obtain the strong edge...
Learning visual representations with self-supervised learning has become popular in computer vision. The idea is to design auxiliary tasks where labels are free to obtain. Most of these tasks end up providing data to learn specific kinds of invariance useful for recognition. In this paper, we propose to exploit different self-supervised approaches to learn representations invariant to (i) inter-instance...
Salient object detection aims to correctly highlight the most salient object(s) in an image. Combining fine-grained contrast prior with rough-grained object consistency, this paper proposes a Focusness Guided Salient object detection (FGS) algorithm. To obtain clean and precise contrast map, FGS uses the focusness prior to guide the contrast map. Combing different saliency priors, FGS utilizes a unified...
Visual sensors are widely used in automatic parking systems, so this paper proposes an algorithm for the visual detection of available parking slots. The proposed system consists of two stages: parking slot recognition and slot occupancy classification. The parking slot recognition stage generates parking slots using the corner features of parking slot markings. The slot occupancy classification stage...
Weakly supervised object localization remains challenging, where only image labels instead of bounding boxes are available during training. Object proposal is an effective component in localization, but often computationally expensive and incapable of joint optimization with some of the remaining modules. In this paper, to the best of our knowledge, we for the first time integrate weakly supervised...
With the development of logistics industry, the logistics automated warehouse is ahead in the race toward the direction of multi-user, multi-variety and flexibility automated warehouse. Traditional AGVs (automatic guided vehicle) are difficult to meet the new demands of logistics warehouse. This paper presents a method to extract the deviation of AGV's navigation path based on threshold segmentation...
We address the problem of recognizing situations in images. Given an image, the task is to predict the most salient verb (action), and fill its semantic roles such as who is performing the action, what is the source and target of the action, etc. Different verbs have different roles (e.g. attacking has weapon), and each role can take on many possible values (nouns). We propose a model based on Graph...
Given an image of a street scene in a city, this paper develops a new method that can quickly and precisely pinpoint at which location (as well as viewing direction) the image was taken, against a pre-stored large-scale 3D point-cloud map of the city. We adopt the recently developed 2D-3D direct feature matching framework for this task [23,31,32,42–44]. This is a challenging task especially for large-scale...
Edge and surface are two fundamental visual elements of an object. The majority of existing object proposal approaches utilize edge or edge-like cues to rank candidates, while we consider that the surface cue containing the 3D characteristic of objects should be captured effectively for proposals, which has been rarely discussed before. In this paper, an object-level proposal model is presented, which...
Fully convolutional neural networks (FCNs) have shown outstanding performance in many dense labeling problems. One key pillar of these successes is mining relevant information from features in convolutional layers. However, how to better aggregate multi-level convolutional feature maps for salient object detection is underexplored. In this work, we present Amulet, a generic aggregating multi-level...
This paper aims to develop an effective flower classification approach using the technology of feature extraction. With this regard, a fused descriptor based on Pyramid Histogram of Visual Words (PHOW) is used to extract the color, texture and contour information of flower image. Secondly, Dictionary Learning and Locality-constrained Linear Coding (LLC) are operated on PHOW feature and then images...
The main challenge of previous saliency detection method is the low quality of obtained saliency map which missed the edge and texture information easily. So it cannot reflect the integrated image salient information. Considering this problem, we propose a novel saliency measure method which combine region contrast and fast guided filter. This method utilizes region contrast method to obtain initial...
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