977 results for “AI Image”

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Research ArticleOpen accessIn the abstractAn Innovative Technique of Texture Classification and Comparison Based on Long Linear PatternsV. Vijaya Kumar, B. Eswara Reddy, U. S.N. Raju, K. Chandra SekharanThe present paper proposes a method of texture classification based on long linear patterns. Linear patterns of long size are bright features defined by morphological properties: linearity, connectivity, width and by a specific Gaussian-like profile whose curvature varies smoothly along the crest line. The most significant information of a texture often appears in the occurrence of grain components. That’s why … …Journal of Computer Science, Vol. 3, Issue 8 · 28 Aug 2007 · 6,720 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHigh-precision Detection of Facial Landmarks to Estimate Head Motions Based on Vision ModelsXiaohong W. Gao, Sergey Anishenko, Dmitry Shaposhnikov et al.A new approach of determination of head movement is presented from the pictures recorded via digital cameras monitoring the scanning processing of PET. Two human vision models of CIECAMs and BMV are applied to segment the face region via skin colour and to detect local facial landmarks respectively. The developed algorithms are evaluated on the pictures (n=12) monitoring a subject’s … …Journal of Computer Science, Vol. 3, Issue 7 · 31 Jul 2007 · 6,819 accessesView PDF Cite

Research ArticleOpen accessIn the abstractLossless Compression Using LFSRsR. Muthiah, K. Neelakantan, Somi SebastianWhile lossy compression techniques are used for images, sound. where feature reproduction is more important than the actual data, it is necessary to use lossless compression for certain files containing data, programmes. Lossless compression techniques are not as effective as lossy ones and usually require a lot of computation for both compression and decompression. We presented a novel lossless compression … …Journal of Computer Science, Vol. 3, Issue 1 · 31 Jan 2007 · 6,999 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Near Real-time Early Warning System on Erosion HazardsFaisal H. Ali, Tew K. HuiWith many incidences of landslides, mudslides and erosion occurrences lately, especially in the highlands in Malaysia, properties were damaged and lives were lost. Seeing the need of resolving and minimizing such untoward incidences, a study has been embarked on developing a near real-time early warning system on erosion hazards so as to provide an early warning to the public, whenever … …American Journal of Environmental Sciences, Vol. 2, Issue 4 · 31 Dec 2006 · 6,706 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFace Recognition using Eigenfaces and Neural NetworksMohamed Rizon, Muhammad Firdaus Hashim, Puteh Saad et al.In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an unknown face by … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 6,940 accessesView PDF Cite

Research ArticleOpen accessIn the abstractApplication of Geo-Information Technology in the Study of Soil and Nutrients Loss by Water Erosion for three Different Land CoverMushtak T. Jabbar, C. A.I. Chong-Fa, Wang Tian-Wei, Shi Zhi-HuaThis research integrated the Revised Universal Soil Loss Equation (RUSLE) and the soil statistical analysis with RS and GIS techniques to quantify soil and nutrient loss risk. The Letianxi watershed, located in the southwest part of Hubei Province of China was taken as a case. A system was established for rating soil erodibility, slope length/gradient, rainfall erosivity and conservation practices. … …American Journal of Applied Sciences, Vol. 2, Issue 6 · 30 Jun 2005 · 6,790 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSoil Degradation Risk Prediction Integrating RUSLE with Geo-information Techniques, the Case of Northern Shaanxi Province in ChinaMushtak T. Jabbar, Xiaoling ChenThis research integrated the Revised Universal Soil Loss Equation (RUSLE) with RS, GIS and GPS techniques to quantify soil erosion risk and the northern part of Shaanxi province in China was taken as a case. A system was established for rating soil erodibility, slope length/gradient, rainfall erosivity and conservation practices. The rating values served as inputs into a modified Revised … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,050 accessesView PDF Cite