Publication NumberUS 20160249047
Assignees
  • K-WILL CORPORATION
Filing StatusPatent Application
US PAIR StatusAbandoned -- Failure to Respond to an Office Action
US PAIR Status Date2018-07-25
Application Number15/031200
AvailabilityUnknown
Filing Date2013-10-23
Publication Date2016-08-25

Abstract

An image inspection method may include sampling a continuous digital image signal by dividing the signal by less than or equal to 20 msec; extracting a high-frequency component from the sampled signal; and detecting an error occurred in an image on the basis of the extracted high-frequency component.

Claims

  • 1. An image inspection method comprising: sampling a continuous digital image signal by dividing the signal by less than or equal to 20 msec; extracting a high-frequency component from the sampled signal; and detecting an error occurred in an image on the basis of the extracted high-frequency component.
  • 2. The image inspection method according to claim 1, further comprising dividing one frame of the digital image signal into a plurality of areas, and detecting the error for each of the areas.
  • 3. The image inspection method according to claim 1, wherein the error is an image disorder, and the extracted high-frequency component is an activity, the activity being an average of the variances of the digital image signal for each block.
  • 4. The image inspection method according to claim 3, wherein when the activity (Vn(t)) is second-order differentiated with respect to time (t) to obtain d2Vn(t)/dt2, if acceleration (d2Vn(t)/dt2)/Vn(t−1) is arranged in order of “positive, negative, and positive” or “negative, positive, and negative” along a time axis, a determination is made that an image disorder has occurred.
  • 5. The image inspection method according to claim 1, wherein when the error is block noise, and if pixel values in an inspection block of the image signal is subjected to orthogonal transformation, and the transformation coefficient satisfies a predetermined condition, a determination is made that block noise has occurred.
  • 6. The image inspection method according to claim 5, wherein when the transformation coefficient satisfies the predetermined condition, a determination is made that a corner has occurred in content displayed by the image signal.
  • 7. The image inspection method according to claim 6, wherein the corner is distinguished between a corner due to block noise and a corner due to the content from the number of corners and a deviation thereof.
  • 8. A sound inspection method comprising: sampling a continuous digital sound signal by dividing the signal by less than or equal to 5 msec; extracting a high-frequency component from the sampled signal; and detecting an error occurred in a sound on the basis of the extracted high-frequency component.
  • 9. The sound inspection method according to claim 8, wherein when the digital sound signal is recorded on a plurality of channels, detecting the error is carried out for each of the channels.
  • 10. The sound inspection method according to claim 8, wherein when sampling is performed at time t along a time axis, frequency conversion is performed on the sampled signal, and n power values Pn(t) and a total power value P(t) in a predetermined bandwidth are obtained, respectively, [1] if the total power value P(t) is higher than a first threshold value, and [2] if a value (P(t)/P(t−T)) produced by dividing the total power value P(t) by total power value P(t−T) at time (t−T) before that time, and a value (P(t)/P(t+T)) produced by dividing the total power value P(t) by total power values P(t+T) at time (t+T) after that time are individually higher than a second threshold value, and [3] if values (Pn(t)/P(T)) produced by dividing the individual power values Pn(t) by the total power value P(T) are higher than a third threshold value, a determination is made that an error has occurred.
  • 11. The sound inspection method according to claim 8, wherein when three power values along a time axis are compared, a first power value Pn(t−T5) and a third power value Pn(t+T+T5) are higher than a fourth threshold value, and a string of second power values Pn(t), . . . , Pn(t+T) is lower than a fifth threshold value, a determination is made that sound skipping has occurred.
  • 12. The sound inspection method according to claim 8, wherein when three power values Pn(t) along a time axis are compared, a first power value Pn(t−T5) and a third power value Pn(t+T+T5) are lower than a sixth threshold value, and a string of second power values Pn(t), . . . , Pn(t+T) is higher than a seventh threshold value, a determination is made that noise has occurred.
  • 13. The image inspection method according to claim 2, wherein the error is an image disorder, and the extracted high-frequency component is an activity, the activity being an average of the variances of the digital image signal for each block.
  • 14. The image inspection method according to claim 2, wherein when the error is block noise, and if pixel values in an inspection block of the image signal is subjected to orthogonal transformation, and the transformation coefficient satisfies a predetermined condition, a determination is made that block noise has occurred.
  • 15. The sound inspection method according to claim 9, wherein when sampling is performed at time t along a time axis, frequency conversion is performed on the sampled signal, and n power values Pn(t) and a total power value P(t) in a predetermined bandwidth are obtained, respectively, [1] if the total power value P(t) is higher than a first threshold value, and [2] if a value (P(t)/P(t−T)) produced by dividing the total power value P(t) by total power value P(t−T) at time (t−T) before that time, and a value (P(t)/P(t+T)) produced by dividing the total power value P(t) by total power values P(t+T) at time (t+T) after that time are individually higher than a second threshold value, and [3] if values (Pn(t)/P(T)) produced by dividing the individual power values Pn(t) by the total power value P(T) are higher than a third threshold value, a determination is made that an error has occurred.
  • 16. The sound inspection method according to claim 9, wherein when three power values along a time axis are compared, a first power value Pn(t−T5) and a third power value Pn(t+T+T5) are higher than a fourth threshold value, and a string of second power values Pn(t), . . . , Pn(t+T) is lower than a fifth threshold value, a determination is made that sound skipping has occurred.
  • 17. The sound inspection method according to claim 9, wherein when three power values Pn(t) along a time axis are compared, a first power value Pn(t−T5) and a third power value Pn(t+T+T5) are lower than a sixth threshold value, and a string of second power values Pn(t), . . . , Pn(t+T) is higher than a seventh threshold value, a determination is made that noise has occurred.
  • 18. The sound inspection method according to claim 10, wherein when three power values along a time axis are compared, a first power value Pn(t−T5) and a third power value Pn(t+T+T5) are higher than a fourth threshold value, and a string of second power values Pn(t), . . . , Pn(t+T) is lower than a fifth threshold value, a determination is made that sound skipping has occurred.
  • 19. The sound inspection method according to claim 10, wherein when three power values Pn(t) along a time axis are compared, a first power value Pn(t−T5) and a third power value Pn(t+T+T5) are lower than a sixth threshold value, and a string of second power values Pn(t), . . . , Pn(t+T) is higher than a seventh threshold value, a determination is made that noise has occurred.