Abstract: A method of correcting the deviation of a position at which a human face is detected using a face detection frame F. An image G within the detection frame F is divided left and right along the portion of the center axis C. The degree of similarity of mirror-symmetrical relationship between the image portions G-1 and G-2 obtained by the division is calculated. An amount of positional deviation d that maximizes the degree of similarity and its direction are found. The frame F is moved a distance corresponding to the amount of positional deviation d in the direction. Thus, the deviation of the detection position due to the detection frame F can be corrected by a quick and simple method.

Abstract: A metadata generating apparatus includes: a private-content-information creating unit that creates content information of an individual; a public-content-information collecting unit that collects public content information for which metadata for retrieval is created; a keyword extracting unit that extracts a keyword, which forms a basis of the metadata for retrieval, from the public content information collected by the public-content-information collecting unit; and a metadata generating unit that generates metadata for retrieval for a private content, which is created by the private-content-information creating unit, on the basis of the keyword extracted by the keyword extracting unit.

Abstract: A printing system includes: a printing device that prints, using ink, an image including a plurality of pixels each assigned with any one of a plurality of tone values; a server device that distributes printing data of a printing image, and first data that represents a total number of pixels of the printing image on a tone value basis; and a client device that receives the printing data and the first data, and based on the first data and second data that represents an amount of ink per pixel needed for the printing device to print each of the tone values, calculates a required amount of ink needed for the printing device to print the printing image.

Abstract: An object image detecting apparatus for determining whether an object image exists in a detection target image includes: an image reading unit reading a predetermined region of the detection target image as a detection target region; a feature vector producing unit dividing an image included in the detection target region resized to a predetermined size into a plurality of blocks, calculating a representative value of an image feature amount indicating a predetermined image feature for each of the divided blocks, and producing a feature vector showing a characteristic of the image feature within the detection target region by referring to the representative value; and at least two classifying units determining whether the object image exists in the detection target region by different references based on the image feature indicated by the feature vector.

Abstract: A chin detecting method is provided. After detecting a human face and setting a chin detecting window at a lower part of the image, an edge strength distribution is calculated within the chin detecting window and pixels having an edge strength with a threshold value or more are detected based on the edge strength distribution. Then an approximated curve is obtained to most match a distribution of each of the detected pixels and a lowermost part of the approximated curve is identified as the lower base of the chin of the human face. Thereby the chin lower base of the human face can be detected automatically, accurately and quickly.

Abstract: A method is provided for extracting a candidate human image region from within a picture image. The top-bottom direction of a picture image containing a human image is discerned. Based on the result of the discernment, the human image is modified to the actual top-bottom direction. Then, the variance values of image features are found about vertical and horizontal lines comprising vertical and horizontal rows of pixels constituting the picture image. Regions having variance values of image features in excess of their threshold values are selected about the vertical and horizontal line directions. An area within the picture image in which the selected regions in the line directions overlap with each other is extracted. Thus, an area within the picture image in which the human image exists can be robustly and quickly extracted.

Abstract: A method of the invention comprises the steps of sequentially selecting a predetermined area within the image G to be searched and then generating an image feature vector for the selection area, inputting the image feature vector into a support vector machine 30 which has learned beforehand the image feature vectors for a plurality of sample images for learning, and deciding whether or not a face image exists in the selection area based on a positional relation with a discrimination hyper-plane. Thereby, it is possible to search an area where a face image exists with high possibility from the image G to be searched at high speed and precisely.

Abstract: A method of correcting the deviation of a position at which a human face is detected using a face detection frame F. An image G within the detection frame F is divided left and right along the portion of the center axis C. The degree of similarity of mirror-symmetrical relationship between the image portions G-1 and G-2 obtained by the division is calculated. An amount of positional deviation d that maximizes the degree of similarity and its direction are found. The frame F is moved a distance corresponding to the amount of positional deviation d in the direction. Thus, the deviation of the detection position due to the detection frame F can be corrected by a quick and simple method.

Abstract: A head-top detecting method is provided for detecting a head-top of a human face from an image with the human face included therein. After detecting a human face and setting a head-top detecting window at an upper part of the image, an image feature quantity within the head-top detecting window is calculated in a vertical direction and a location in which the image feature quantity changes with a threshold value or more is identified as the head-top of the human face. Thereby the head-top of a human face can be detected accurately and quickly.

Abstract: A face image detecting method, detecting system and detecting program are provided. After dividing the detection target area into a plurality of blocks and dimensionally compressing the area, feature vectors including a representative value in each block are calculated and then a discriminator detects whether the face image exists or not in the detection target area by using the feature vectors. The discriminator detects after an image feature quantity is dimensionally compressed to the extent of not damaging the feature of face image. Since the number of image feature items to be used for discrimination is substantially reduced from the number of pixels within the detection target area to that of blocks, the number of operations drastically decreases and a face image can be quickly detected.

Abstract: A sample image is filtered through a circumferential filter 28, an image feature amount is learned in a discrimination section 30, an image G to be searched is filtered through the circumferential filter 28 to detect a rotation invariant image feature amount for each filtered area, and each detected image feature amount is inputted into the discrimination section 30. Thereby, it is discriminated whether or not a filtering area is considered to be face image at high speed. And the dimensional number of image feature amounts is greatly reduced, so that not only the discrimination work but also the learning time of the sample image are greatly reduced.

Abstract: An image retrieving system is provided which is suitable for acquiring a retrieving result or a classifying result according to the desire of a user. The system extracts a noticing area from a retrieving key image and each retrieving object image, and a characteristic vector V of these images is generated on the basis of the extracted noticing area. An image similar to the retrieving key image is retrieved from a retrieving object image registration database on the basis of the generated characteristic vector V.