Method and device of object detectable and background removal, and storage media for storing program thereof

A method of object detectable and background removal for enabling an object to be automatically detected minutely and accurately as far as contours comprising the steps of:

• using an image consisting of a virtually even background and an object of detection target as an input image, by way of an input process of said image;
• calculating a statistic in every respective sectional images, while dividing said input image into sectional images, by way of a statistic calculation process;
• selecting a sectional image including only said background based on said statistic calculated previously in said statistic calculation process, by way of a background only sectional image selection process;
• estimating a statistic of a whole picture from said statistic of said sectional image including only said background, by way of a statistic estimation process;
• determining a threshold in the whole picture from said estimated statistic, by way of a threshold determination process;
• and
• comparing said threshold determined in the whole picture with said input image, by way of a comparison process, wherein said method causes said object of detection target to be isolated from said input image,
• wherein said statistic calculation process includes a sectional image division process for dividing said input image into sectional images, and a mean value and standard deviation calculation process for calculating a skewness from a mean value and a standard deviation of a prescribed characteristic value of a sectional image.

A device of object detectable and background removal for enabling an object to be automatically detected minutely and accurately as far as contours comprising:

• a sectional image statistic calculation means for calculating a mean value and a standard deviation of the prescribed characteristic value of said sectional image while dividing to be processed an input image into sectional images;
• a background sectional image selection means for judging a sectional image whose standard deviation is of the smallest value in said sectional images as a sectional image whose probability of including only a background is high, subsequently, comparing a standard deviation of the prescribed characteristic value of said sectional image with a standard deviation of the prescribed characteristic value of another sectional image, thus judging a sectional image having a standard deviation whose difference between the standard deviation concerned and another standard deviation is less than a threshold as a sectional image including only the background;
• a background statistic estimation means for investigating all of mean values and standard deviations in the sectional images including only the background and in another sectional images by way of the background estimated previously, further in the sectional images including only the background located in the neighborhood of the sectional image, and in the sectional image by way of the background estimated previously in another sectional image;
• and
• a threshold generation object detectable and background removal means wherein in order to isolate an object to be removed background by using the mean value and the standard deviation in the whole sectional images, a second threshold is calculated to be defined in such a way that also a constant set beforehand is multiplied by the standard deviation of the prescribed characteristic value of the background estimated previously, then the above multiplied value is added to a mean value of the prescribed characteristic value of the background estimated previously, subsequently, calculating it all over the pictures to be outputted, thus judging pixels within the threshold as a background while using said two kinds of thresholds and judging pixels without the threshold as an object of detection target,
• wherein said prescribed characteristic value is at least one of a brightness, a color information, and an edge information.

A device of object detectable and background removal for enabling an object to be automatically detected minutely and accurately as far as contours, using an image consisting of a virtually even background and an object of detection target as an input, said device roughly consisting of four means of a sectional image statistic calculation means, a background sectional image selection means, a background statistic estimation means, and a threshold generation object detectable and background removal means,

• said sectional image statistic calculation means comprising:
• a sectional image division means for dividing an input image into sectional images to be outputted;
• a mean value and standard deviation and skewness calculation means for calculating to be outputted a mean value, a standard deviation, and a skewness of a prescribed characteristic value in every respective sectional images, with the sectional image signal as inputs;
• and
• a sectional image statistic storage means for storing to be outputted a mean value, a standard deviation, and a skewness of the prescribed characteristic value of the respective sectional images whenever necessary, using the mean value and the standard deviation, and the skewness of the prescribed characteristic value of said sectional images as inputs,
• said background sectional image selection means comprising:
• a skewness threshold and minimum standard deviation criterion background only sectional image selection means for outputting a sectional image whose absolute value of the skewness is less than a threshold given beforehand in the sectional images, and whose standard deviation of the prescribed characteristic value is of the smallest value by way of a sectional image whose probability of including only a background is high, using the mean value and the standard deviation, and the skewness of the prescribed characteristic value of said sectional images as inputs;
• a background only sectional image selection means judging to be outputted a sectional image having the standard deviation whose difference is less than the threshold between the standard deviation of the prescribed characteristic value of the sectional image whose probability of including only the background is high and the standard deviation of the prescribed characteristic value in the sectional images, and whose absolute value of skewness is less than the threshold given beforehand by way of a sectional image including only a background;
• and
• a background only sectional image statistic storage means for storing the location of the sectional image including only the background and the mean value and the standard deviation of the prescribed characteristic value of the sectional image concerned, thus outputting them whenever necessary,
• said background statistic estimation means comprising:
• a background-exception sectional image selection means, when a command is entered in order to investigate sectional images except a background, investigating the mean value and the standard deviation of the prescribed characteristic value of the sectional image including only the background, and the mean value and the standard deviation of the prescribed characteristic value by way of the estimated background of another sectional images, then, if there exists a sectional image whose mean value and standard deviation of the prescribed characteristic value by way of a background is not estimated, outputting the sectional image concerned, while if the mean value and the standard deviation of the prescribed characteristic value by way of the background in respect to the whole sectional images are specified, issuing a command so as to generate a threshold for the sake of object detectable and background removal;
• a neighborhood background only sectional image existence judgement means investigating the mean values and the standard deviations of the prescribed characteristic values both of the sectional images except backgrounds and the sectional images including only background located in the neighborhood of said sectional images, and the mean values and the standard deviations of the prescribed characteristic value by way of the estimated background of another sectional images, even though when there exists only one sectional image whose mean value and standard deviation of the prescribed characteristic value are estimated in the neighborhood thereof, issuing a command so as to estimate a mean value and a standard deviation of the prescribed characteristic value of the sectional image except the background, while when there exist no sectional image whose mean value and standard deviation of the prescribed characteristic value are estimated, issuing a command so as to select next sectional image;
• a mean value and standard deviation interpolation/extrapolation means, when a command is entered in order to estimate a mean value and a standard deviation of the prescribed characteristic value in the sectional image except the background, thus estimating to be outputted by averaging the mean value and the standard deviation of the prescribed characteristic value of the sectional image including only the background in the neighborhood thereof, and the mean value and the standard deviation of the prescribed characteristic value by way of the estimated background of the sectional image in the neighborhood thereof, simultaneously outputting an estimated sectional image selection command signal so as to select next sectional image;
• and
• an estimated statistic storage means for storing to be outputted the mean value and the standard deviation of the prescribed characteristic value estimated previously whenever necessary,
• said threshold generation object detectable and background removal means comprising:
• a threshold generation means calculating to be outputted a first threshold and a second threshold over the whole picture, when a command is entered in order to calculate the threshold after the mean value and the standard deviation of the prescribed characteristic value by way of the background in the whole partial images had been estimated, in which a first threshold is obtained in such a way that it causes a standard deviation multiplied by a constant given beforehand to be subtracted from the mean value by using the mean value and the standard deviation of the prescribed characteristic by way of the estimated background in the whole sectional images for the sake of detecting object and removing background, and a second threshold is obtained in such a way that it causes a standard deviation multiplied by a constant given beforehand to be added to the mean value;
• and
• a threshold processing means judging pixels involved between two thresholds as a background, and judging another pixels as an object of detection target by using said two thresholds.

A device of object detectable and background removal for enabling an object to be automatically detected minutely and accurately as far as contours, with an image constituted by virtually even background and an object of detection target, said device including a sectional image statistic calculation means, a background sectional image selection means, a background statistic estimation means, and a threshold generation object detectable and background removal means,

• said sectional image statistic calculation means comprising:
• a sectional image division means for dividing input images into sectional images;
• a mean value and a standard deviation calculation means which calculates to be outputted a mean value and a standard deviation of the prescribed characteristic value in every respective sectional images with said sectional image signals as inputs;
• and
• a sectional image statistic storage means storing to be outputted the mean value and the standard deviation of the prescribed characteristic value of respective sectional images with the mean value and the standard deviation of the prescribed characteristic value of said sectional images as inputs,
• said background sectional image selection means comprising:
• a minimum standard deviation reference background only sectional image selection means for outputting a sectional image whose standard deviation of the prescribed characteristic value is of the most smallest value among sectional images as a sectional image whose probability of including only a background is high with the mean value and the standard deviation of the prescribed characteristic value of the sectional image;
• a background only sectional image selection means comparing a standard deviation of the prescribed characteristic value of a sectional image whose probability of including only the background is high with a standard deviation of the prescribed characteristic value in another sectional images, thus judging to be outputted a partial image having standard deviation whose difference between the standard deviation concerned and a standard deviation of the prescribed characteristic value of a sectional image whose probability of including only said background is less than a threshold as a sectional image including only a background;
• and
• a background only sectional image statistic storage means storing a location of the sectional image including only said background and the mean value and the standard deviation of the prescribed characteristic value of the sectional image concerned to output them whenever necessary,
• said background statistic estimation means comprising:
• a background-exception sectional image selection means, when a command for investigating a sectional image except a background enters thereto, investigating both of a mean value and a standard deviation of the prescribed characteristic value in a sectional image including only a background and a mean value and a standard deviation of the prescribed characteristic value by way of an estimated background in another sectional images, if there exists a sectional image whose no estimated value of a mean value and a standard deviation of the prescribed characteristic value by way of a background exists, outputting the partial image concerned, in case where a mean value and a standard deviation of the prescribed characteristic value are estimated with regard to whole sectional images, so that said background statistic estimation means issues a command of generating a threshold for the sake of object detectable and background removal;
• a neighborhood background only sectional image existence judgment means investigating mean values and standard deviations both of sectional images including images with the exception of a background and sectional images including only a background located in the neighborhood of said sectional images, and investigating mean values and standard deviations of the prescribed characteristic value by way of a background estimated previously in another sectional images, when there exists a sectional image whose only one set of a mean value and a standard deviation of the prescribed characteristic value are estimated in the neighborhood thereof, thus issuing a command so as to estimate a mean value and a standard deviation of the prescribed characteristic value of a sectional image except said background;
• a mean value and standard deviation interpolation/extrapolation means, when receiving a command to estimate a mean value and a standard deviation of the prescribed characteristic value in the sectional image except said background, estimating to be outputted by averaging both of mean values and standard deviations of the prescribed characteristic value of a sectional image including only the background in the neighborhood thereof, simultaneously, outputting an estimated sectional image selection command signal so as to select next sectional image;
• and
• an estimated statistic storage means storing the mean value and the standard deviation of the prescribed characteristic value estimated previously to be outputted whenever necessary, and
• said threshold generation object detectable and background removal means comprising:
• a threshold generation means, when a command for calculating a threshold is entered therein after completing whole mean values and standard deviations of the prescribed characteristic value in the whole sectional images, by using the mean value and the standard deviation in the whole sectional images, a second threshold is calculated to be defined in such a way that also a constant set beforehand is multiplied by the standard deviation of the prescribed characteristic value of the background estimated previously, then the above multiplied number is added to a mean value of the prescribed characteristic value of the background estimated previously, subsequently, calculating it all over the pictures to be outputted;
• and
• a threshold processing means judging pixels within the threshold as a background while using said two kinds of thresholds and judging pixels without the threshold as an object of detection target,
• wherein said prescribed characteristic value is at least one of a brightness, a color information, and an edge information.