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 in regard to isolation of only said object of detection target at said comparison process, when said comparison process implements threshold processing in the respective location of the pixels, firstly a first threshold is calculated to be defined in such a way that 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 subtracted from a mean value of the prescribed characteristic value of the background estimated previously, secondly 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, thus in case where the prescribed characteristic value of said location of the pixel is larger than the first threshold and is smaller than the second threshold, judging said pixel as the background, so that said comparison process removes the background to isolate the object due to the fact that said comparison process causes the same processing to be executed over the whole pixels.

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 roughly consisting 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 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 judgement 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.