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This paper introduces Adaptive Feature Thresholding (AFT) which is a novel method of person-dependent off-line signature verification. AFT enhances how a simple image feature of a signature is converted to a binary feature vector by significantly improving its representation in relation to the training signatures. The similarity between signatures is then(More)
A novel method of face gender classifier construction is proposed and evaluated. Previously, researchers have assumed that a computationally expensive face alignment step (in which the face image is transformed so that facial landmarks such as the eyes, nose, chin, etc, are in uniform locations in the image) is required in order to maximize the accuracy of(More)
This paper presents a new approach for the object categorization problem. Our model is based on the successful dasiabag of wordspsila approach. However, unlike the original model, image features (keypoints) are not seen as independent and orderless. Instead, our model attempts to discover intermediate representations for each object class. This approach(More)
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