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The proposed features can be formed by extracting the phase congruency information for each pixel in the three-color image channels. The maximum phase congruency values are selected from the corresponding color channels. Histograms of the phase congruency values of the local regions in the image are computed with respect to its orientation. These histograms are concatenated to construct the proposed descriptor. Results of the experiments performed on the proposed descriptor show that it has better detection performance and lower error rates than a set of the state of the art feature extraction methodologies.<\/p>","DOI":"10.4018\/ijmstr.2016070104","type":"journal-article","created":{"date-parts":[[2017,2,7]],"date-time":"2017-02-07T10:50:36Z","timestamp":1486464636000},"page":"52-72","source":"Crossref","is-referenced-by-count":0,"title":["Local Phase Features in Chromatic Domain for Human Detection"],"prefix":"10.4018","volume":"4","author":[{"given":"Hussin K.","family":"Ragb","sequence":"first","affiliation":[{"name":"University of Dayton, Dayton, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vijayan K.","family":"Asari","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJMSTR.2016070104-0","unstructured":"Basavaraj, G., & Reddy, G. 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