Studies were conducted on the effects of grain angle on reproducibility and accurate measurement of moisture content of four wood samples using a pin-style moisture meter. The wood samples were partitioned into four q...Studies were conducted on the effects of grain angle on reproducibility and accurate measurement of moisture content of four wood samples using a pin-style moisture meter. The wood samples were partitioned into four quadrants and moisture contents were measured along the grain direction in the first and second quadrants from 0 degree to 150 degrees insteps of 30 degrees. Experimental results indicated that the average moisture content remained constant as the grain angle increased. Repeated measurements of moisture content at different grain angles or points on the wood surface showed similar patterns of variation. Within-point standard deviations of the moisture contents were greater than between-point standard deviations. A non-destructive method of measuring moisture content at the same location or point on the wood surfaces could not be proposed because of the high variation of moisture content when repeated measurements were taken at the same point. Instead, accurate measurements of moisture content could be obtained at random positions within a radius of 30 mm from the point of intersection of the moisture content axis and the grain angle.展开更多
An algorithm for automatically extracting feature points is developed after the area of feature points in 2-dimensional (2D) imagebeing located by probability theory, correlated methods and criterion for abnormity. Fe...An algorithm for automatically extracting feature points is developed after the area of feature points in 2-dimensional (2D) imagebeing located by probability theory, correlated methods and criterion for abnormity. Feature points in 2D image can be extracted only by calculating standard deviation of gray within sampled pixels area in our approach statically. While extracting feature points, the limitation to confirm threshold by tentative method according to some a priori information on processing image can be avoided. It is proved that the proposed algorithm is valid and reliable by extracting feature points on actual natural images with abundant and weak texture, including multi-object with complex background, respectively. It can meet the demand of extracting feature points of 2D image automatically in machine vision system.展开更多
文摘Studies were conducted on the effects of grain angle on reproducibility and accurate measurement of moisture content of four wood samples using a pin-style moisture meter. The wood samples were partitioned into four quadrants and moisture contents were measured along the grain direction in the first and second quadrants from 0 degree to 150 degrees insteps of 30 degrees. Experimental results indicated that the average moisture content remained constant as the grain angle increased. Repeated measurements of moisture content at different grain angles or points on the wood surface showed similar patterns of variation. Within-point standard deviations of the moisture contents were greater than between-point standard deviations. A non-destructive method of measuring moisture content at the same location or point on the wood surfaces could not be proposed because of the high variation of moisture content when repeated measurements were taken at the same point. Instead, accurate measurements of moisture content could be obtained at random positions within a radius of 30 mm from the point of intersection of the moisture content axis and the grain angle.
文摘An algorithm for automatically extracting feature points is developed after the area of feature points in 2-dimensional (2D) imagebeing located by probability theory, correlated methods and criterion for abnormity. Feature points in 2D image can be extracted only by calculating standard deviation of gray within sampled pixels area in our approach statically. While extracting feature points, the limitation to confirm threshold by tentative method according to some a priori information on processing image can be avoided. It is proved that the proposed algorithm is valid and reliable by extracting feature points on actual natural images with abundant and weak texture, including multi-object with complex background, respectively. It can meet the demand of extracting feature points of 2D image automatically in machine vision system.
