Algorithm of Color Detection for Moving Video Objects Based on Mode Matching

2012 ◽  
Vol 239-240 ◽  
pp. 1000-1003
Author(s):  
Zhao Quan Cai ◽  
Hui Hu ◽  
Tao Xu ◽  
Wei Luo ◽  
Yi Cheng He

It is urgent to study how to effectively identify color of moving objects from the video in the information era. In this paper, we present the color identification methods for moving objects on fixed camera. One kind of the methods is background subtraction that recognizes the foreground objects by compare the difference of pixel luminance between the current image and the background image at the same coordinates. Another kind is based on the statistics of HSV color and color matching which makes the detection more similar to the color identification of the human beings. According to the experiment results, after the completion of the background modelling, our algorithm of background subtraction, statistics of the HSV color and the color matching have strong color recognition ability on the moving objects of video.

2014 ◽  
Vol 556-562 ◽  
pp. 3549-3552
Author(s):  
Lian Fen Huang ◽  
Qing Yue Chen ◽  
Jin Feng Lin ◽  
He Zhi Lin

The key of background subtraction which is widely used in moving object detecting is to set up and update the background model. This paper presents a block background subtraction method based on ViBe, using the spatial correlation and time continuity of the video sequence. Set up the video sequence background model firstly. Then, update the background model through block processing. Finally employ the difference between the current frame and background model to extract moving objects.


2017 ◽  
Vol 11 (3) ◽  
pp. 98
Author(s):  
Ahmed Mustafa Taha Alzbier ◽  
Hang Cheng

As the present computer vision technology is growing up, and the multiple RGB color object tracking is considered as one of the important tasks in computer vision and technique that can be used in many applications such as surveillance in a factory production line, event organization, flow control application, analysis and sort by colors and etc. In video processing applications, variants of the background subtraction method are broadly used for the detection of moving objects in video sequences. The background subtraction is the most popular and common approach for motion detection. However , this is paper presents our investigation the first objective of the whole algorithm chain is to find the RGB color within a video. The idea from the beginning was to look for certain specific features of the patches, which would allow distinguishing red, green and blue color objects in the image. In this paper an algorithm is proposed to track the real time moving RGB color objects using kinect camera. We will use a kinect camera to capture the real time video and making an image frame from this video and extracting red, green and blue color .Here image processing is done through MATLAB for color recognition process each color. Our method can tracking accurately at 95% in real-time.


Author(s):  
Rekha V. ◽  
Natarajan K. ◽  
Innila Rose J.

Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.


2011 ◽  
Vol 143-144 ◽  
pp. 721-725
Author(s):  
Zhao Quan Cai ◽  
Wei Luo ◽  
Zhong Nan Ren ◽  
Han Huang

In the presented paper, we proposed a common color model and designed the color judgment method, which is based on the HSV model. This method will translate the RGB values of the points in video images to HSV values, and use HSV values to recognize the color. After that, software of real-time video object recognition was developed based on color features, which is also based on their search of target color identification. Besides, the system is developed by VC based on OpenCV, which has achieved the goal of real-time video motion detection and object color recognition. Finally, the experimental results indicate that the algorithm is accurate and similar to human recognition of the moving objects in videos view, which demonstrates the good performance of the target identification and color judgment.


2018 ◽  
Vol 12 (6) ◽  
pp. 3626-3633
Author(s):  
Pravesh Kumar Goel ◽  
Paresh P. Kotak ◽  
Amit Gupta

The moving object detection from a stationary video sequence is a primary task in various computer vision applications. In this proposed system; three processing levels are suppose to perform: detects moving objects region from the background image; reduce noise from the pixels of detected region and extract meaningful objects and their features (area of object, center point of area etc.). In this paper; background subtraction techniques is used for segments moving objects from the background image, which is capable for pixel level processing. Morphology operation (Erosion and dilation) are used to remove pixel to pixel noise. In last level, CCL algorithm is used for sorts out foregrounds pixels are grouped into meaningful connected regions and their features.


2012 ◽  
Vol 263-266 ◽  
pp. 2211-2216
Author(s):  
Qing Ye ◽  
Yong Mei Zhang

Moving target detection and tracking algorithm as the core issue of computer vision and human-computer interaction is the first step of intelligent video surveillance system. Through comparing temporal difference method and background subtraction, a moving object detection and tracking algorithm based on background subtraction under static background is proposed, in order to quickly and accurately detect and identify the moving object in the intelligent monitoring system. In this algorithm, firstly, we use background acquisition method to receive the background image, then use the current frame image and the received background image to perform background subtraction in order to extract foreground object information and receive the difference image; secondly, we use threshold segmentation and morphology image processing to process the difference image in order to eliminate noises and receive the clear binary moving object image; finally, we use the centroid tracking method to track and mark the moving object. Experimental results show that the algorithm can effectively and quickly detect and track moving object from video sequence under static background. This algorithm is easily realized and has good real-time and robust, which is automated and self triggered for background updating. The algorithm can be used in driver assistance systems, motion capture, virtual reality and other fields.


Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8374
Author(s):  
Yupei Zhang ◽  
Kwok-Leung Chan

Detecting saliency in videos is a fundamental step in many computer vision systems. Saliency is the significant target(s) in the video. The object of interest is further analyzed for high-level applications. The segregation of saliency and the background can be made if they exhibit different visual cues. Therefore, saliency detection is often formulated as background subtraction. However, saliency detection is challenging. For instance, dynamic background can result in false positive errors. In another scenario, camouflage will result in false negative errors. With moving cameras, the captured scenes are even more complicated to handle. We propose a new framework, called saliency detection via background model completion (SD-BMC), that comprises a background modeler and a deep learning background/foreground segmentation network. The background modeler generates an initial clean background image from a short image sequence. Based on the idea of video completion, a good background frame can be synthesized with the co-existence of changing background and moving objects. We adopt the background/foreground segmenter, which was pre-trained with a specific video dataset. It can also detect saliency in unseen videos. The background modeler can adjust the background image dynamically when the background/foreground segmenter output deteriorates during processing a long video. To the best of our knowledge, our framework is the first one to adopt video completion for background modeling and saliency detection in videos captured by moving cameras. The F-measure results, obtained from the pan-tilt-zoom (PTZ) videos, show that our proposed framework outperforms some deep learning-based background subtraction models by 11% or more. With more challenging videos, our framework also outperforms many high-ranking background subtraction methods by more than 3%.


2020 ◽  
Vol 17 (6) ◽  
pp. 472-478
Author(s):  
Wei-tao Gong ◽  
Wei-dong Qu ◽  
Guiling Ning

Two pyridinium amide-based receptors L1 and L2 with a small difference of H-bond position of the amide have been synthesized and characterized. Interestingly, they exhibited a huge difference in sensing towards AcO- and H2PO4 -, respectively. Receptor L1 was found to be ‘naked-eye’ selective for AcO- anions, while receptor L2 showed clear fluorescence enhancement selective to H2PO4 - anion. The recognition ability has been established by fluorescence emission, UV-vis spectra, and 1HNMR titration.


2014 ◽  
Vol 533 ◽  
pp. 218-225 ◽  
Author(s):  
Rapee Krerngkamjornkit ◽  
Milan Simic

This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.


Problemos ◽  
2009 ◽  
Vol 76 ◽  
pp. 52-65
Author(s):  
Vytautas Rubavičius

Straipsnyje grindžiama nuomonė, jog postmodernybė yra iš modernybės kylantis kapitalizmo sistemos būvis, kuriam būdinga gyvybės suprekinimas ir suišteklinimas. Postmodernybę charakterizuoja populiariosios ir medijų kultūros išplitimas. Tos kultūros apima ne tik kultūros prekes, bet ir vartojimo būdus, įgūdžius ir jų lavinimą. Pastaruoju metu jos kuria nemirtingumo vaizdiniams bei nuojautoms palankią kultūrinę, intelektinę ir pasaulėvaizdinę terpę, kurioje struktūriškai įsitvirtina genetinis diskursas ir jo nustatomos žmogaus ir jo gyvenamo pasaulio aiškinimo gairės. Svarbus šio diskurso bruožas yra technologinis inžinerinis jo pobūdis, išryškėjęs susiejant nano ir biotechnologijas, kuriomis tikimasi įveikti gyvąją ir negyvąją gamtą skiriančią prarają, iš reikalingų atomų bei molekulių kuriant reikalingų ląstelių dalis ir klonuojant gyvas būtybes. Gyvybė suprekinama ir suišteklinama patentuojant gyvybės elementus – genus ir su jais susijusius procesus. Daroma išvada, jog visi genetikos, informatikos ir kitų mokslų laimėjimai, teikiantys žmogaus gyvenimo ilginimo galimybių, kurios palaiko gundančią nemirtingumo idėją, jau yra persmelkti prekinių santykių, tad ir pats nemirtingumas įmanomas tik kaip prekė. Aptariami kai kurie evoliuciniai ir religiniai techno sapiens sampratos aspektai. Detaliau gvildenamos dvi „nemirtingumo“ versijos: Z. Baumano, kuris nemirtingumo pažadą sieja su kompiuterinės technikos plėtra prasidėjus „Antrajai medijų erai“, ir J. Baudrillard’o, tegiančio, jog klonavimo technologijos „apgręžia“ evoliuciją ir žmogų gundo virusiniu ar vėžiniu belyčiu nemirtingumu.Pagrindiniai žodžiai: genetinis diskursas, klonavimas, medijų kultūra, nanobiotechnologijos, nemirtingumas, suprekinimas.Genetic Discourse in Media Culture: Temptation by Commodified ImmoralityVytautas Rubavičius   SummaryPostmodernity is maintained as a stage of the development of capitalism. The difference between modernity and postmodernity is explained in relation to the new sphere of commodification and resourcification, namely, that of life and of all natural living processes. Postmodern media culture, or popular culture, is peopled by signs of immortality and various kinds of immortals – cyborgs, clones, zombies, immortal human beings and others. Thus, culture accustoms a consumer to immortals and immortality which is concidered as the main goal of a human being and evolution. By nano-bio-technologies and genetic discourse this goal is made scientifically valid, thus reachable. Genetic discourse is becoming the fundamental world-view providing focal landmarks for the emerging future. Media culture supports the spreading of genetic discourse and facilitates its understanding. The temptation by immortality can be considered as a version of modernist ideology of human liberation from various natural, social and heavenly bonds. This liberation, and also secularization, is supported by a scientific genetic technological discourse which is becoming a stimulating factor of postmodern media production. The genetic explanation of the world is particularly handy for technological reflexivity: the entire world is as if encapsulated into human genes, which become the principle explaining the mystery of life, evolution and the future of humanity, thus rendering power to produce the human proper form and the future of people. All the possibilities stemming from the new genetic and biotech discoveries fell under the regulation of property relations by patenting, thus making “immortality” – as a temptation and brand – not only an exeptional commodity, but also a political tool and a commodifying force. As the relationships of private property have penetrated natural biogenetic diversity and, having turned it into a resource, the cognitive subject has reached the goal to secularise the Universe, which he has set for himself: only he as the owner and producer of genes lures people with the eternal shapes of the clones and their genetic information, which will be sustained in any location of the Universe. The temptation by “immortality” will become even stronger when the genetic code is mastered. The future of humanity is related to the mixed forms of life, trans-genic or otherwise genetically modified organisms and techno-human forms that will help to postpone, and later to conquer, death. Even thinkers with religious tendencies perceive the technological improvement of human beings as their evolution towards the techno sapiens and consider such a development as an advancement towards the Kingdom of God. The technologization of human beings is imagined in terms of their divination. Yet in this case the character of contemporary science secularising God and obliterating the perception of divinity is overlooked. Two versions of immortality are analyzed more closely – that of Z. Bauman, who links it with the development of computer technologies, and that of J. Baudrillard, who gives a warning that by cloning technologies humanity is trying to inverse the evolution and to return to the undifferentiated state of cells. The conclusion is drawn that regardless of how we understand ‘immortality,’ argue over its reality or unreality, all possibilities to prolong human life granted by genetics, informatics and other advances in science and technologies, which support the tempting idea of immortality, have already been penetrated by commodity relationships; therefore, “immortality” itself will be available only as a commodity.Keywords: cloning, commodification, genetic discourse, immortality, media culture, nano-bio-technologies.


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