Two-dimensional ultrasonic flaw detection based on the wavelet packet transform
An important issue in ultrasonic nondestructive evaluation is the detection of flaw echoes in the presence of coherent background noise associated with the microstructure of materials. Many signal processing techniques have proven to be useful for this purpose, but fully 2-D flaw detection technique...
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| Veröffentlicht in: | IEEE transactions on ultrasonics, ferroelectrics, and frequency control ferroelectrics, and frequency control, 1997-11, Vol.44 (6), p.1382-1394 |
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| container_title | IEEE transactions on ultrasonics, ferroelectrics, and frequency control |
| container_volume | 44 |
| creator | Robini, M.C. Magnin, I.E. Benoit-Cattin, H. Baskurt, A. |
| description | An important issue in ultrasonic nondestructive evaluation is the detection of flaw echoes in the presence of coherent background noise associated with the microstructure of materials. Many signal processing techniques have proven to be useful for this purpose, but fully 2-D flaw detection techniques remain desirable. In this paper, we describe a novel automatic flaw detection method based on the wavelet packet transform, which is particularly well adapted to B-scan image analysis. After a brief review of the essential elements of the theory of wavelets and wavelet packets, a detailed description of the method is provided. The detection process operates on a set of spatially oriented frequency channels, i.e., detail images, obtained from successive wavelet packet decompositions of the initial B-scan. A statistical selection procedure based on the modeling of the detail image histograms retains the useful information-bearing frequency channels. The flaw information is then extracted from these selected channels by means of a specific thresholding scheme. Some experimental detection results in B-scan images of austenitic stainless steel samples comprising artificial flaws are presented. |
| doi_str_mv | 10.1109/58.656642 |
| format | Article |
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Many signal processing techniques have proven to be useful for this purpose, but fully 2-D flaw detection techniques remain desirable. In this paper, we describe a novel automatic flaw detection method based on the wavelet packet transform, which is particularly well adapted to B-scan image analysis. After a brief review of the essential elements of the theory of wavelets and wavelet packets, a detailed description of the method is provided. The detection process operates on a set of spatially oriented frequency channels, i.e., detail images, obtained from successive wavelet packet decompositions of the initial B-scan. A statistical selection procedure based on the modeling of the detail image histograms retains the useful information-bearing frequency channels. The flaw information is then extracted from these selected channels by means of a specific thresholding scheme. 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Many signal processing techniques have proven to be useful for this purpose, but fully 2-D flaw detection techniques remain desirable. In this paper, we describe a novel automatic flaw detection method based on the wavelet packet transform, which is particularly well adapted to B-scan image analysis. After a brief review of the essential elements of the theory of wavelets and wavelet packets, a detailed description of the method is provided. The detection process operates on a set of spatially oriented frequency channels, i.e., detail images, obtained from successive wavelet packet decompositions of the initial B-scan. A statistical selection procedure based on the modeling of the detail image histograms retains the useful information-bearing frequency channels. The flaw information is then extracted from these selected channels by means of a specific thresholding scheme. Some experimental detection results in B-scan images of austenitic stainless steel samples comprising artificial flaws are presented.</description><subject>Acoustical measurements and instrumentation</subject><subject>Acoustics</subject><subject>Background noise</subject><subject>Data mining</subject><subject>Exact sciences and technology</subject><subject>Frequency</subject><subject>Fundamental areas of phenomenology (including applications)</subject><subject>Histograms</subject><subject>Image analysis</subject><subject>Microstructure</subject><subject>Physics</subject><subject>Signal processing</subject><subject>Wavelet analysis</subject><subject>Wavelet packets</subject><subject>Wavelet transforms</subject><issn>0885-3010</issn><issn>1525-8955</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1997</creationdate><recordtype>article</recordtype><recordid>eNqNkc1Lw0AQxRdRsFYPXj3lIIKH1J39yu5Ril9Q6KWew2Z3FqPbpGZTi_-9KSle9TQD7_cewzxCLoHOAKi5k3qmpFKCHZEJSCZzbaQ8JhOqtcw5BXpKzlJ6pxSEMGxClqtdm_t6jU2q28bGbBv7zqa2qV0Wot1lHnt0_aBllU3os2Hp3zDb2S-M2Gcb6z6GMXiaFNpufU5Ogo0JLw5zSl4fH1bz53yxfHqZ3y9yx5Xuc2554auCgtQUg3PUevScsSC11gDSWcN05UB64byjvgreg3fcVEAFRcan5GbM3XTt5xZTX67r5DBG22C7TSXTWmmh-D9ApQxo-BsUBRhZyAG8HUHXtSl1GMpNV69t910CLfcllFKXYwkDe30ItcnZGIY3uTr9GhhVhRH7I69GrEbEX_WQ8QM1QI8p</recordid><startdate>19971101</startdate><enddate>19971101</enddate><creator>Robini, M.C.</creator><creator>Magnin, I.E.</creator><creator>Benoit-Cattin, H.</creator><creator>Baskurt, A.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>7SP</scope><scope>7QQ</scope><scope>8BQ</scope><scope>JG9</scope></search><sort><creationdate>19971101</creationdate><title>Two-dimensional ultrasonic flaw detection based on the wavelet packet transform</title><author>Robini, M.C. ; Magnin, I.E. ; Benoit-Cattin, H. ; Baskurt, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-3a37db701580efcc0aded322f5888115ca928bc15d4cdc0dbfdd1dc39b1040e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1997</creationdate><topic>Acoustical measurements and instrumentation</topic><topic>Acoustics</topic><topic>Background noise</topic><topic>Data mining</topic><topic>Exact sciences and technology</topic><topic>Frequency</topic><topic>Fundamental areas of phenomenology (including applications)</topic><topic>Histograms</topic><topic>Image analysis</topic><topic>Microstructure</topic><topic>Physics</topic><topic>Signal processing</topic><topic>Wavelet analysis</topic><topic>Wavelet packets</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Robini, M.C.</creatorcontrib><creatorcontrib>Magnin, I.E.</creatorcontrib><creatorcontrib>Benoit-Cattin, H.</creatorcontrib><creatorcontrib>Baskurt, A.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Electronics & Communications Abstracts</collection><collection>Ceramic Abstracts</collection><collection>METADEX</collection><collection>Materials Research Database</collection><jtitle>IEEE transactions on ultrasonics, ferroelectrics, and frequency control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Robini, M.C.</au><au>Magnin, I.E.</au><au>Benoit-Cattin, H.</au><au>Baskurt, A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Two-dimensional ultrasonic flaw detection based on the wavelet packet transform</atitle><jtitle>IEEE transactions on ultrasonics, ferroelectrics, and frequency control</jtitle><stitle>T-UFFC</stitle><date>1997-11-01</date><risdate>1997</risdate><volume>44</volume><issue>6</issue><spage>1382</spage><epage>1394</epage><pages>1382-1394</pages><issn>0885-3010</issn><eissn>1525-8955</eissn><coden>ITUCER</coden><abstract>An important issue in ultrasonic nondestructive evaluation is the detection of flaw echoes in the presence of coherent background noise associated with the microstructure of materials. Many signal processing techniques have proven to be useful for this purpose, but fully 2-D flaw detection techniques remain desirable. In this paper, we describe a novel automatic flaw detection method based on the wavelet packet transform, which is particularly well adapted to B-scan image analysis. After a brief review of the essential elements of the theory of wavelets and wavelet packets, a detailed description of the method is provided. The detection process operates on a set of spatially oriented frequency channels, i.e., detail images, obtained from successive wavelet packet decompositions of the initial B-scan. A statistical selection procedure based on the modeling of the detail image histograms retains the useful information-bearing frequency channels. The flaw information is then extracted from these selected channels by means of a specific thresholding scheme. Some experimental detection results in B-scan images of austenitic stainless steel samples comprising artificial flaws are presented.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/58.656642</doi><tpages>13</tpages></addata></record> |
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| identifier | ISSN: 0885-3010 |
| ispartof | IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 1997-11, Vol.44 (6), p.1382-1394 |
| issn | 0885-3010 1525-8955 |
| language | eng |
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| source | IEEE Xplore (Online service) |
| subjects | Acoustical measurements and instrumentation Acoustics Background noise Data mining Exact sciences and technology Frequency Fundamental areas of phenomenology (including applications) Histograms Image analysis Microstructure Physics Signal processing Wavelet analysis Wavelet packets Wavelet transforms |
| title | Two-dimensional ultrasonic flaw detection based on the wavelet packet transform |
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