Color Video Compression Based on Fractal Coding Using Quadtree Weighted Finite Automata

Kamble, Shailesh D.; Thakur, Nileshsingh V.; Malik, Latesh; Bajaj, Preeti

doi:10.1007/978-81-322-2247-7_66

Cited by 9 publications

(13 citation statements)

References 11 publications

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“…Block matching algorithms are widely adopted due to the motion analysis of obcects, tracking the obcects and also in video compression and processing [28] [34]. Block matching motion estimation is used for the video compression and fractal coding [33,34]. The standards for video compression are utilized for the video coding.…”

Section: Related Work On Object Tracking Using Block Matching Algmentioning

confidence: 99%

Overview of Object Detection and Tracking based on Block Matching Techniques

Samdurkar¹,

Kamble²,

Thakur³

et al. 2017

Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering

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-Object tracking is one of the vital fields of computer vision that detects the moving object from a video sequence. Object detection is used to detect the object present in the video and to find the exact location of that object. The object tracking can be applied in various fields that include video surveillance, robot vision, traffic monitoring, automated civil or military surveillance system, traffic monitoring, human-computer interaction, vehicle navigation, biomedical image analysis, medical imaging and much more. The object tracking algorithm requires tracking the object in each frame of the video. A common approach is to use the background subtraction, which eliminates the common static background, resulting into foreground region showing the presence of the desired object. Block matching technique is the most popular technique for computing the motion vectors between the two frames of video sequences and different searching techniques are available to compute motion vectors between frames. Still, there is a scope for improvement in modifying or developing a new shape pattern for block matching motion estimation to find out and track the object in the video. This paper presents the several object detection and tracking methods and how block matching can be used to track object from a video.

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Section: Related Work On Object Tracking Using Block Matching Algmentioning

confidence: 99%

Overview of Object Detection and Tracking based on Block Matching Techniques

Samdurkar¹,

Kamble²,

Thakur³

et al. 2017

Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering

Self Cite

View full text Add to dashboard Cite

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“…This method of GFA allows any combination of rotations, flips, and complementation of the quadrant image [62]. Quad-tree based EWFA coding is used in fractal color video compression technique [66]. The quadtree partitioning scheme is used to specify the address of each sub-images i.e.…”

Section: Related Work On Automata Theorymentioning

confidence: 99%

“…The main difference between circular prediction mapping and non-contractive inter-frame mapping is that circular prediction mapping should be contractive for the iterative decoding process to converge, while non-contractive interframe mapping needs not be contractive since the decoding depends on the already decoded frames and is non-iterative [66]. Recently, Wang [67] proposed a hybrid fractal video compression algorithm, which merges the advantages of a cube-based fractal compression method and a frame-based fractal compression method; in addition, an adaptive partition instead of fixed-size partition is discussed.…”

Section: Related Work On Motion Estimationmentioning

confidence: 99%

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Kamble¹,

Thakur²,

Bajaj³

2016

IJIMAI

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---Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression.

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“…Estimation of Motion vector (MV) by reducing the size of the blocks can also make the tracking process fast [20]. The various applications of block matching algorithm other than tracking are used in video compression [21], block matching motion estimation using automata theory for fractal coding [22,23] and also modified Three-Step Search (TSS) algorithm using fractal coding [24]. The various sections of this paper are organized as follows: Algorithm and analysis of DS and CDS are given in Section II.…”

mentioning

confidence: 99%

Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm

Samdurkar¹,

Kamble²,

Thakur³

et al. 2018

IJIMAI

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Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS) and cross diamond search algorithms (CDS) are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS) algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS) in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time.

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Color Video Compression Based on Fractal Coding Using Quadtree Weighted Finite Automata

Cited by 9 publications

References 11 publications

Overview of Object Detection and Tracking based on Block Matching Techniques

Overview of Object Detection and Tracking based on Block Matching Techniques

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm

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