scholarly journals Extracting Objects Using Contour Evolutions in Edge-Based Object Tracking

2006 ◽  
Vol 10 (3) ◽  
pp. 362-371
Author(s):  
Hiroyuki Tsuji ◽  
◽  
Shinji Tokumasu ◽  
Hiroki Takahashi ◽  
Masayuki Nakajima ◽  
...  
Keyword(s):  
Evolution Equations ◽  
Good Condition ◽  
Video Object ◽  
Edge Image ◽  
Object Contour ◽  
Contour Evolution ◽  
Edge Based ◽  
Binary Object ◽  
Binary Edge ◽  
Evolution Approach

We propose edge-based object extraction targeting automatic video object plane (VOP) generation in MPEG-4 content-based video coding. In an edge-based VOP generation framework proposed by Meier, the object is represented as a binary edge image that does not generally form a closed contour and that also contains many extra edges, making extracting the object contour accurately less straightforward in such situations. To solve this problem, we adopt a PDE-based contour evolution approach to evolve initial multiple contours contained inside the object toward its boundary based on evolution equations, and to finally merge them into a single contour that accurately represents the object’s shape. Our experimental results using an MPEG standard image sequence show that object contours obtained as we propose appear subjectively more natural in shape compared with those obtained by two conventional methods, especially when the binary object model is not in good condition.

scholarly journals Reversible Data Hiding Scheme Using Adaptive Block Truncation Coding Based on an Edge-Based Quantization Approach

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 765 ◽  
Author(s):  
Chia-Chen Lin ◽  
Ching-Chun Chang ◽  
Zhi-Ming Wang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Zero Point ◽  
Edge Image ◽  
Block Truncation Coding ◽  
Canny Edge ◽  
High Embedding Capacity ◽  
Processing Block ◽  
And Performance ◽  
Edge Based

In this paper, we provide a novel reversible data hiding method using adaptive block truncation coding based on an edge-based quantization (ABTC-EQ) approach. We exploit the characteristic not being used in ABTC-EQ. To accomplish this, we first utilized a Canny edge detector to obtain an edge image and classify each block in a cover image into two versions, edge-block and non-edge-block. Subsequently, k-means clustering was used to obtain three quantization levels and derive the corresponding bit map while the current processing block was the case of an edge-block. Then Zero-Point Fixed Histogram Shifting (ZPF-HS) was applied to embed the secret information into compressed code. The experimental results show that our method provides a high embedding capacity for each test image and performance is better than other methods.

scholarly journals OBJECT CONTOUR COMPLETION BY COMBINING OBJECT RECOGNITION AND LOCAL EDGE CUES

2017 ◽  
Author(s):  
Kar Seng Loke
Keyword(s):  
Optimization Procedure ◽  
Specific Information ◽  
Top Down ◽  
Bottom Up ◽  
Object Contour ◽  
Contour Feature ◽  
Edge Based ◽  
Local Edge ◽  
Initial Object ◽  
Contour Completion

We developed a top-down and bottom-up segmentation ofobjects using shape contours through a two-stage procedure. First, the object was identified using an edge-based contour feature and then the object contour was obtained using a constraint optimization procedure based on the results from the earlier identified contours. The initial object detection provides object category specific information for the contour completion to be effected. We argue that top-down bottom-up interaction architecture has plausible neurological correlates. This method has an advantage in that it does not require learning boundaries with large datasets.  

Fast Content Based Color Image Retrieval System Based on Texture Analysis of Edge Map

2011 ◽  
Vol 341-342 ◽  
pp. 168-172
Author(s):  
Hesamoddin Salehian ◽  
Fatemeh Zamani ◽  
Mansour Jamzad
Keyword(s):  
Time Complexity ◽  
Retrieval System ◽  
Color Image ◽  
Color Spaces ◽  
Edge Detector ◽  
Complementary Information ◽  
Edge Image ◽  
Image Retrieval System ◽  
Different Color ◽  
Binary Edge

In this paper we propose a method for CBIR based on the combination of texture, edge map and color. As texture of edges yields important information about the images, we utilized an adaptive edge detector that produces a binary edge image. Also, using the statistics of color in two different color spaces provides complementary information to retrieve images. Our method is time efficient since we have applied texture calculations on the binary edge image. Our experimental results showed both the higher accuracy and lower time complexity of our method with similar related works using SIMPLIcity database.

Fast and Effective Algorithm of Iris Localization Based on Hough Transform

2014 ◽  
Vol 519-520 ◽  
pp. 788-793
Author(s):  
Bao Qiang Wang ◽  
Lin Zhang
Keyword(s):  
Hough Transform ◽  
Polar Coordinates ◽  
Effective Algorithm ◽  
Horizontal Edge ◽  
Edge Image ◽  
Iris Localization ◽  
Boundary Parameter ◽  
Relationship Of ◽  
Binary Edge

The purpose of the paper is to research a fast and effective algorithm of iris localization based on Hough transform, for improving the quality of iris localization. The methods of practice include as follows. Firstly, the pupil center is estimated by using of a metric. Secondly, the binary edge image is transformed into the polar coordinates. After the rules of horizontal edge selection are used to select horizontal edge, the edge-selected image is transformed into the Cartesian coordinates. Finally, the Hough transform and the coupling relationship of the boundaries are used to determine the parameters of boundaries, and the biggest boundary parameter is selected for the estimation of the iris boundary parameter. Experiments indicate that the proposed algorithm is effective and available.

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