{"title":"边缘直方图描述子与Contourlet变换相结合的SBIR方法","authors":"N. Chaudhary","doi":"10.18701/IMSMANTHAN.V11I01.6880","DOIUrl":null,"url":null,"abstract":"This paper focuses on the problem of efficient and fast retrieval of\nimages from a large database using sketch as query image.\nBasically searching is based on a descriptor that addresses the\nasymmetry between binary sketch from the user side and full\ncolor image of the database. The working of proposed algorithm\nis such that query image and full color database images undergo\nsame feature extraction process. Database images will be\nclustered offline which reduces time complexity on runtime.\nFurther indexing is done which will be used to describe, store\nand organize image information and to assist people in finding\nimage resources conveniently and quickly. Firstly feature vector\nextraction is done using contours and then edges will be detected\nin different orientation using modulus maxima edge detection in\ncontourlet domain. This approach is almost better than existing\napproaches in many aspects such as compactness of feature\nvector, simplicity of implementation, retrieval performance and\nefficient feature extraction less time complexity.","PeriodicalId":135569,"journal":{"name":"The Journal of Innovations","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Combined Approach to SBIR using Edge Histogram Descriptor with Contourlet Transform\",\"authors\":\"N. Chaudhary\",\"doi\":\"10.18701/IMSMANTHAN.V11I01.6880\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on the problem of efficient and fast retrieval of\\nimages from a large database using sketch as query image.\\nBasically searching is based on a descriptor that addresses the\\nasymmetry between binary sketch from the user side and full\\ncolor image of the database. The working of proposed algorithm\\nis such that query image and full color database images undergo\\nsame feature extraction process. Database images will be\\nclustered offline which reduces time complexity on runtime.\\nFurther indexing is done which will be used to describe, store\\nand organize image information and to assist people in finding\\nimage resources conveniently and quickly. Firstly feature vector\\nextraction is done using contours and then edges will be detected\\nin different orientation using modulus maxima edge detection in\\ncontourlet domain. This approach is almost better than existing\\napproaches in many aspects such as compactness of feature\\nvector, simplicity of implementation, retrieval performance and\\nefficient feature extraction less time complexity.\",\"PeriodicalId\":135569,\"journal\":{\"name\":\"The Journal of Innovations\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Innovations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18701/IMSMANTHAN.V11I01.6880\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Innovations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18701/IMSMANTHAN.V11I01.6880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Combined Approach to SBIR using Edge Histogram Descriptor with Contourlet Transform
This paper focuses on the problem of efficient and fast retrieval of
images from a large database using sketch as query image.
Basically searching is based on a descriptor that addresses the
asymmetry between binary sketch from the user side and full
color image of the database. The working of proposed algorithm
is such that query image and full color database images undergo
same feature extraction process. Database images will be
clustered offline which reduces time complexity on runtime.
Further indexing is done which will be used to describe, store
and organize image information and to assist people in finding
image resources conveniently and quickly. Firstly feature vector
extraction is done using contours and then edges will be detected
in different orientation using modulus maxima edge detection in
contourlet domain. This approach is almost better than existing
approaches in many aspects such as compactness of feature
vector, simplicity of implementation, retrieval performance and
efficient feature extraction less time complexity.