An Improved Active Contour Model for Salient Object Detection Using Edge Cues

2018 ◽  
pp. 365-375
Author(s):  
Gargi Srivastava ◽  
Rajeev Srivastava
Keyword(s):  
Object Detection ◽  
Active Contour ◽  
Active Contour Model ◽  
Salient Object Detection ◽  
Salient Object ◽  
Contour Model

scholarly journals Active Contour Model Using Fast Fourier Transformation for Salient Object Detection

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 192
Author(s):  
Umer Sadiq Khan ◽  
Xingjun Zhang ◽  
Yuanqi Su
Keyword(s):  
Object Detection ◽  
Fourier Transformation ◽  
Active Contour ◽  
Active Contour Model ◽  
Salient Object Detection ◽  
Fast Fourier Transformation ◽  
Salient Object ◽  
Active Contour Models ◽  
Contour Model ◽  
Contour Models

The active contour model is a comprehensive research technique used for salient object detection. Most active contour models of saliency detection are developed in the context of natural scenes, and their role with synthetic and medical images is not well investigated. Existing active contour models perform efficiently in many complexities but facing challenges on synthetic and medical images due to the limited time like, precise automatic fitted contour and expensive initialization computational cost. Our intention is detecting automatic boundary of the object without re-initialization which further in evolution drive to extract salient object. For this, we propose a simple novel derivative of a numerical solution scheme, using fast Fourier transformation (FFT) in active contour (Snake) differential equations that has two major enhancements, namely it completely avoids the approximation of expansive spatial derivatives finite differences, and the regularization scheme can be generally extended more. Second, FFT is significantly faster compared to the traditional solution in spatial domain. Finally, this model practiced Fourier-force function to fit curves naturally and extract salient objects from the background. Compared with the state-of-the-art methods, the proposed method achieves at least a 3% increase of accuracy on three diverse set of images. Moreover, it runs very fast, and the average running time of the proposed methods is about one twelfth of the baseline.

Small object detection in cluttered image using a correlation based active contour model

2012 ◽  
Vol 33 (5) ◽  
pp. 543-553 ◽  
Author(s):  
Alireza Vard ◽  
Kamal Jamshidi ◽  
Naser Movahhedinia
Keyword(s):  
Object Detection ◽  
Active Contour ◽  
Active Contour Model ◽  
Small Object ◽  
Contour Model ◽  
Small Object Detection

scholarly journals Active Contours in the Complex Domain for Salient Object Detection

2020 ◽  
Vol 10 (11) ◽  
pp. 3845
Author(s):  
Umer Sadiq Khan ◽  
Xingjun Zhang ◽  
Yuanqi Su
Keyword(s):  
Object Detection ◽  
Active Contour ◽  
Salient Object Detection ◽  
Complex Domain ◽  
Salient Object ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Active Contour Models ◽  
Spatial Frequencies ◽  
Contour Models

The combination of active contour models (ACMs) for both contour and salient object detection is an attractive approach for researchers in image segmentation. Existing active contour models fail when improper initialization is performed. We propose a novel active contour model with salience detection in the complex domain to address this issue. First, the input image is converted to the complex domain. The complex transformation gives salience cue. In addition, it is well suited for cyclic objects and it speeds up the iteration of the active contour. During the process, we utilize a low-pass filter that lets the low spatial frequencies pass, while attenuating, or completely blocking, the high spatial frequencies to reduce the random noise connected with favorable or higher frequencies. Furthermore, the model introduces a force function in the complex domain that dynamically shrinks a contour when it is outside of the object of interest and expands it when the contour is inside the object. Comprehensive tests on both synthetic images and natural images show that our proposed algorithm produces accurate salience results that are close to the ground truth. At the same time, it eliminates re-initialization and, thus, reduces the execution time.

Feature-based active contour model and occluding object detection

2016 ◽  
Vol 33 (4) ◽  
pp. 648 ◽  
Author(s):  
Sara Memar ◽  
Riadh Ksantini ◽  
Boubakeur Boufama
Keyword(s):  
Object Detection ◽  
Active Contour ◽  
Active Contour Model ◽  
Contour Model ◽  
Feature Based

scholarly journals CHACT: Convex Hull Enabled Active Contour Technique for Salient Object Detection

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 22441-22451 ◽  
Author(s):  
Maheep Singh ◽  
M. C. Govil ◽  
Emmanuel Shubhakar Pilli
Keyword(s):  
Convex Hull ◽  
Object Detection ◽  
Active Contour ◽  
Salient Object Detection ◽  
Salient Object ◽  
Contour Technique
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