Chin detecting method, chin detecting system and chin detecting program for a chin of a human face

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.

Description

RELATED APPLICATIONS [0001] This application claims priority to Japanese Patent Application No. 2003-407911 filed Dec. 5, 2003 which is hereby expressly incorporated by reference herein in its entirety. BACKGROUND [0002] 1. Technical Field [0003] The present invention concerns pattern recognition and object recognition technologies, and more specifically, the invention relates to a chin detecting method, a chin detecting system and a chin detecting program for accurately detecting the location of the chin of a human face from an image of the human face. [0004] 2. Related Art [0005] With recent advancements in pattern recognition technologies and information processors such as computers, the recognition accuracy of text and sound has been dramatically improved. However, in the pattern recognition of an image of a human, an object, the landscape and so on, e.g., an image scanned from a digital still camera and the like, it is still difficult to accurately and quickly identify whether ...

AI Technical Summary

Benefits of technology

[0019] In the invention as described above, after selecting a part with a high possibility of including the chin of a human face and setting the chin detecting window at that part, the edge strength distribution within the chin detecting window is calculated. In other words, an outline including the chin lower base generally has a higher edge strength than that of the periphery of the outline due to a sharp contrast between the outline and the periphery thereof. Consequently, it becomes possible to easily and reliably select a candidate area to be the outline including the chin lower base that should be included in the chin detecting window by calculating the edge strength distribution within the chin detecting window.

[0043] Thereby since it becomes possible to obtain the same effect as in Aspects 2 and 8 and to realize the function in software as in Aspect 9, the function can be realized economically and easily. In addition, version upgrades can be easily attained such as a change and an improvement of the function.

Problems solved by technology

However, in the pattern recognition of an image of a human, an object, the landscape and so on, e.g., an image scanned from a digital still camera and the like, it is still difficult to accurately and quickly identify whether a human face is visible in the image or not.

However, it is impractical to retake a photo simply because the size and location of the face in the photo is slightly out of regulation, although it may be rational if the human face is not facing the front or if an accessory such as a hat is worn.

This causes a problem of imposing considerable labor and cost on a user.

Thereby it becomes possible to detect a robust chin lower base by accurately and quickly detecting an outline of the chin of the human face, which is difficult to detect from a face image.

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