Robust coastal region detection method using image segmentation and sensor LOS information for infrared search and track

2013 ◽  
Author(s):  
Sungho Kim ◽  
Sun-Gu Sun ◽  
Soon Kwon ◽  
Kyung-Tae Kim
Keyword(s):  
Image Segmentation ◽  
Detection Method ◽  
Coastal Region ◽  
Region Detection

The Detection Method of Lane Line Based on the Improved Otsu Threshold Segmentation

2015 ◽  
Vol 741 ◽  
pp. 354-358 ◽  
Author(s):  
Yang Shan Tang ◽  
Dao Hua Xia ◽  
Gui Yang Zhang ◽  
Li Na Ge ◽  
Xin Yang Yan
Keyword(s):  
Image Segmentation ◽  
Processing Time ◽  
Detection Method ◽  
Segmentation Algorithm ◽  
Test Results ◽  
Threshold Segmentation ◽  
Otsu Method ◽  
Time Requirements ◽  
Lane Line ◽  
Center Distance

For overcoming the shortage of Otsu method, proposed an improved Otsu threshold segmentation algorithm. On the basis of Otsu threshold segmentation algorithm, the gray level was divided into two classes according to the image segmentation, to determine the best threshold by comparing their center distance, so as to achieve peak line recognition under the condition of multiple gray levels. Then did experiments on image segmentation of the lane line with MATLAB by traditional Otsu threshold segmentation algorithm and the improved algorithm, the threshold of traditional Otsu threshold segmentation algorithm is 144 and the threshold of the improved Otsu threshold segmentation algorithm is 131, the processing time is within 0.453 s. Test results show that the white part markings appear more, the intersection place of white lines and the background is more clear, so this method can identify lane markings well and meet the real-time requirements.

Multi-Resolution Salient Region Detection in Frequency Domain

2014 ◽  
Vol 6 (1) ◽  
pp. 60-70
Author(s):  
Yingchun Guo ◽  
Yanhong Feng ◽  
Gang Yan ◽  
Shuo Shi
Keyword(s):  
Frequency Domain ◽  
Euclidean Distance ◽  
Detection Method ◽  
Saliency Map ◽  
Normal Distribution Function ◽  
Salient Region Detection ◽  
Salient Region ◽  
Region Detection ◽  
Proposed Model ◽  
Salient Regions

Salient region detection is a challenge problem in computer vision, which is useful in image segmentation, region-based image retrieval, and so on. In this paper we present a multi-resolution salient region detection method in frequency domain which can highlight salient regions with well-defined boundaries of object. The original image is sub-sampled into three multi-resolution layers, and for each layer the luminance and color salient features are extracted in frequency domain. Then, the significant values are calculated by using invariant laws of Euclidean distance in Lab space and the normal distribution function is used to specify the salient map in each layer in order to remove noise and enhance the correlation among the vicinity pixels. The final saliency map is obtained by normalizing and merging the multi-resolution salient maps. Experimental evaluation depicts the promising results from the proposed model by outperforming the state-of-art frequency-tuned model.

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