吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1709-1716.doi: 10.13229/j.cnki.jdxbgxb201505047

Previous Articles     Next Articles

Image salient region detection algorithm based on contrast and spatial location

ZHANG Wen-jie1, XIONG Qing-yu2   

  1. 1.College of Automation, Chongqing University, Chongqing 400030, China;
    2.The School of Software Engineering, Chongqing University, Chongqing 401331, China
  • Received:2014-03-10 Online:2015-09-01 Published:2015-09-01

Abstract: A bottom-up data driven algorithm is proposed to extract image salient region by utilizing visual saliency prior knowledge such as regional contrast and spatial location etc. In this algorithm, first, the foreground region in the image is extracted. Then, the regional contrast and spatial position feature functions are constructed. Finally, the saliency map is acquired by fusing these features. The model well establishes the relationship between the spatial space and regional contrast, and generates saliency maps with precise details. The results demonstrate that the proposed method consistently outperforms existing saliency detection algorithms, suppresses non-significant regional disturbance, and yields higher consistent saliency map, when evaluated using one of the large publicly available data sets MSRA-1000. Meanwhile, the extracted saliency map is applied to automatically segment saliency region and better segmentation results are obtained.

Key words: information processing, saliency detection, salient region, image contrast, spatial location

CLC Number: 

  • TN911
[1] Jiang H, Wang J, Yuan Z, et al. Salient object detection: a discriminative regional feature integration approach[C]∥IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, 2013: 2083-2090.
[2] Jian M W, Dong J Y, Ma J. Image retrieval using wavelet-based salient regions[J]. Imaging Science Journal, 2011, 59(4): 219-231.
[3] 李勇,陈贺新,耿晓东,等. 基于目标区域定位和特征融合的图像检索算法[J]. 吉林大学学报:工学版, 2008(增刊2):217-220. Li Yong, Chen He-xin, Geng Xiao-dong, et al. Image retrieval algorithm based on object region location and feature fusion[J]. Journal of Jilin University (Engineering and Technology Edition), 2008(Sup.2):217-220.
[4] Rutishauser U, Walther D, Koch C, et al. Is bottom-up attention useful for object recognition?[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Washington, 2004: 37-44.
[5] Ko B C, Nam J. Object-of-interest image segmentation based on human attention and semantic region clustering[J]. JOSA A,2006, 23(10): 2462-2470.
[6] Yang J, Yang M H. Top-down visual saliency via joint crf and dictionary learning[C]∥IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, 2012: 2296-2303.
[7] Liu T, Yuan Z, Sun J, et al. Learning to detect a salient object[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(2): 353-367.
[8] Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259.
[9] Ma Y F, Zhang H J. Contrast-based image attention analysis by using fuzzy growing[C]∥Proceedings of the Eleventh ACM International Conference on Multimedia. ACM, New York, 2003: 374-381.
[10] Harel J, Koch C, Perona P. Graph-based visual saliency[C]∥Advances in Neural Information Processing System,Vancouver,Canada,2007:545-552.
[11] Hou X, Zhang L. Saliency detection: A spectral residual approach[C]∥IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, 2007: 1-8.
[12] Achanta R, Hemami S, Estrada F, et al. Frequency-tuned salient region detection[C]∥IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, 2009: 1597-1604.
[13] Stas Goferman, Lihi Zelnik-Manor, Ayellet Tal. Context-aware saliency detection[J]. IEEE Trans Pattern Anal Mach Intell,2012, 34(10): 1915-1926.
[14] 黄志勇,何发智,蔡贤涛,等.一种随机的视觉显著性检测算法[J].中国科学:信息科学,2011,41(7):863-874. Huang Zhi-yong, He Fa-zhi, Cai Xian-tao, et al. Efficient random saliency map detection[J]. Science China Information Sciences, 2011, 41(7): 863-874.
[15] 郭迎春,袁浩杰,吴鹏. 基于Local特征和Regional特征的图像显著性检测[J].自动化学报,2013,39(8):1214-1224. Guo Ying-Chun, Yuan Hao-Jie, WU Peng. Image saliency detection based on local and regional features[J]. Acta Automation Sinica,2013,39(8):1214-1224.
[16] Liu Z, Zou W, Li L, et al. Co-Saliency detection based on hierarchical segmentation[J]. IEEE Signal Processing Letters, 2014, 21(1):88-92.
[17] Fu H, Cao X, Tu Z. Cluster-based co-saliency detection[J]. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society, 2013, 22(10): 3766-3778.
[18] Xie Y, Lu H, Yang M. Bayesian saliency via low and mid level cues[J].Transactions on Image Processing, 2013,22(5):1689-1698.
[19] Cheng M M, Zhang G X, Mitra N J, et al. Global contrast based salient region detection[C]∥IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, 2011: 409-416.
[20] Achanta R, Estrada F, Wils P, et al. Salient region detection and segmentation[C]∥6th International Conference on Computer Vision System,Santorini,Greece,2008:66-75.
[21] Ohashi T, Aghbari Z, Makinouchi A. Hill-climbing algorithm for efficient color-based image segmentation[C]∥IASTED International Conference on Signal Processing, Pattern Recognition, and Applications,Rhodes, 2003: 17-22.
[22] Li X, Lu H, Zhang L, et al. Saliency detection via dense and sparse reconstruction[C]∥IEEE International Conference on Computer Vision (ICCV), Sydney, 2013:2976-2983.
[23] Yang C, Zhang L, Lu H, et al. Saliency detection via graph-based manifold ranking[C]∥IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, 2013: 3166-3173.
[24] Lempitsky V, Kohli P, Rother C, et al. Image segmentation with a bounding box prior[C]∥IEEE International Conference on Computer Vision (ICCV), Kyoto, 2009: 277-284.
[25] Grady L, Jolly M P, Seitz A. Segmentation from a box[C]∥IEEE International Conference on Computer Vision (ICCV), Barcelona, 2011: 367-374.
[26] Einhäuser W, König P. Does luminance-contrast contribute to a saliency map for overt visual attention?[J]. European Journal of Neuroscience,2003, 17(5): 1089-1097.
[27] Judd T, Ehinger K, Durand F, et al. Learning to predict where humans look[C]∥IEEE 12th International Conference on Computer Vision, Kyoto, 2009: 2106-2113.
[28] 李茜. 图像的显著性特征提取[D]. 上海:上海大学通信与信息工程学院,2008. Li Qian. Saliency image feature extraction[D]. Shanghai:School of Communication and Information Engineering, Shanghai University, 2008.
[29] Achanta R, Susstrunk S. Saliency detection using maximum symmetric surround[C]∥the 17th IEEE International Conference on Image Processing (ICIP), Hong Kong, 2010: 2653-2656.
[30] Zhai Y, Shah M. Visual attention detection in video sequences using spatiotemporal cues[C]∥Proceedings of the 14th Annual ACM International Conference on Multimedia. ACM, New York, 2006: 815-824.
[31] Han J, Ngan K N, Li M, et al. Unsupervised extraction of visual attention objects in color images[J]. IEEE Transactions on Circuits and Systems for Video Technology,2006, 16(1): 141-145.
[32] Rother C, Kolmogorov V, Blake A. Grabcut: interactive foreground extraction using iterated graph cuts[C]∥ACM Transactions on Graphics (TOG),ACM, New York, 2004:309-314.
[33] Boykov Y Y, Jolly M P. Interactive graph cuts for optimal boundary & region segmentation of objects in ND images[C]∥Proceedings of the Eighth IEEE International Conference on Computer Vision, Vancouver, 2001: 105-112.
[1] YING Huan,LIU Song-hua,TANG Bo-wen,HAN Li-fang,ZHOU Liang. Efficient deterministic replay technique based on adaptive release strategy [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1917-1924.
[2] LIU Zhong-min,WANG Yang,LI Zhan-ming,HU Wen-jin. Image segmentation algorithm based on SLIC and fast nearest neighbor region merging [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1931-1937.
[3] SHAN Ze-biao,LIU Xiao-song,SHI Hong-wei,WANG Chun-yang,SHI Yao-wu. DOA tracking algorithm using dynamic compressed sensing [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1938-1944.
[4] YAO Hai-yang, WANG Hai-yan, ZHANG Zhi-chen, SHEN Xiao-hong. Reverse-joint signal detection model with double Duffing oscillator [J]. 吉林大学学报(工学版), 2018, 48(4): 1282-1290.
[5] QUAN Wei, HAO Xiao-ming, SUN Ya-dong, BAI Bao-hua, WANG Yu-ting. Development of individual objective lens for head-mounted projective display based on optical system of actual human eye [J]. 吉林大学学报(工学版), 2018, 48(4): 1291-1297.
[6] CHEN Mian-shu, SU Yue, SANG Ai-jun, LI Pei-peng. Image classification methods based on space vector model [J]. 吉林大学学报(工学版), 2018, 48(3): 943-951.
[7] CHEN Tao, CUI Yue-han, GUO Li-min. Improved algorithm of multiple signal classification for single snapshot [J]. 吉林大学学报(工学版), 2018, 48(3): 952-956.
[8] MENG Guang-wei, LI Rong-jia, WANG Xin, ZHOU Li-ming, GU Shuai. Analysis of intensity factors of interface crack in piezoelectric bimaterials [J]. 吉林大学学报(工学版), 2018, 48(2): 500-506.
[9] LIN Jin-hua, WANG Yan-jie, SUN Hong-hai. Improved feature-adaptive subdivision for Catmull-Clark surface model [J]. 吉林大学学报(工学版), 2018, 48(2): 625-632.
[10] WANG Ke, LIU Fu, KANG Bing, HUO Tong-tong, ZHOU Qiu-zhan. Bionic hypocenter localization method inspired by sand scorpion in locating preys [J]. 吉林大学学报(工学版), 2018, 48(2): 633-639.
[11] YU Hua-nan, DU Yao, GUO Shu-xu. High-precision synchronous phasor measurement based on compressed sensing [J]. 吉林大学学报(工学版), 2018, 48(1): 312-318.
[12] WANG Fang-shi, WANG Jian, LI Bing, WANG Bo. Deep attribute learning based traffic sign detection [J]. 吉林大学学报(工学版), 2018, 48(1): 319-329.
[13] LIU Dong-liang, WANG Qiu-shuang. Instantaneous velocity extraction method on NGSLM data [J]. 吉林大学学报(工学版), 2018, 48(1): 330-335.
[14] TANG Kun, SHI Rong-hua. Detection of wireless sensor network failure area based on butterfly effect signal [J]. 吉林大学学报(工学版), 2017, 47(6): 1939-1948.
[15] LI Juan, MENG Ke-xin, LI Yue, LIU Hui-li. Seismic signal noise suppression based on similarity matched Wiener filtering [J]. 吉林大学学报(工学版), 2017, 47(6): 1964-1968.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!