EXPERIMENTAL STUDY ON LIP AND SMILE DETECTION

This paper presents a lip and smile detection method based-on the normalized RGB chromaticity diagram. The method employs the popular Viola-Jones detection method to detect the face. To avoid the false positive, the eye detector is introduced in the detection stage. Only the face candidates with the detected eyes are considered as the face. Once the face is detected, the lip region is localized using the simple geometric rule. Further, the the red color thresholding based-on the normalized RGB chromaticity diagram is proposed to extract the lip. The projection technique is employed for detecting the smile state. From the experiment results, the proposed method achieves the lip detection rate of 97% and the smile detection rate of 94%. Paper ini menyajikan medote pendeteksi bibir dan senyum berdasarkan diagram tingkat kromatis RGB ternormalisasi. Metode ini menggunakan metode Viola-Jones yang populer untuk mendeteksi wajah. Untuk menghindari kesalahan positif, detektor mata diperkenalkan pada tahapan deteksi. Hanya kandidat wajah dengan mata yang telah terdeteksi yang dianggap sebagai wajah. Setelah wajah dideteksi, bagian bibir ditempatkan dengan menggunakan aturan geometris sederhana. Selanjutnya, batasan warna merah berdasarkan pada diagram kromatisitas RGB ternormalisasi digunakan untuk mengekstrak bibir. Teknik proyeksi digunakan untuk mendeteksi keadaan tersenyum. Dari hasil percobaan, metode yang diusulkan mencapai 97% untuk tingkat deteksi bibir dan 94% untuk tingkat deteksi senyum

A Directed FCM Approach for Analysis of Stained Tissues

The use of digital imagery has increased phenomenally especially in the clinical field. These images are obtained from different modalities such as X-ray and MRI. Digital imaging of the more traditional imagery such as stained tissues has opened up new means of investigation. Hence a need to build a system to analyze the stained tissues and extract the salient information has risen. A Directed FCM Approach for Analysis of Stained Tissues introduces a modified FCM to analyze the tissues. The analysis can be controlled by the user by selecting the number of clusters, size of the clusters and the centers for the clusters. The results of this analysis are reported as the percent of changes in a specific square area

LIP DETECTION BASED-ON NORMALIZED RGB CHROMATICITY DIAGRAM

This paper presents a new lip detection method based-on normalized RGB chromaticity diagram. The method consists of three stages: face detection, lip region localization and lip detection. The popular Viola-Jones face detection technique is employed in the face detection stage. In the lip detection stage, lip color is extracted using our novel color segmentation method that exploits the distribution of lip color on the RGB chromaticity diagram. From the experiment using 100 face images, the detection rate of 97% is achieved

LIP DETECTION BASED-ON NORMALIZED RGB CHROMATICITY DIAGRAM

ABSTRACT This paper presents a new lip detection method based-on normalized RGB chromaticity diagram. The method consists of three stages: face detection, lip region localization and lip detection. The popular Viola-Jones face detection technique is employed in the face detection stage. In the lip detection stage, lip color is extracted using our novel color segmentation method that exploits the distribution of lip color on the RGB chromaticity diagram. From the experiment using 100 face images, the detection rate of 97% is achieved. Keywords: Face detection, lip detection, color segmentation, chromaticity diagram

Visual Passwords Using Automatic Lip Reading

This paper presents a visual passwords system to increase security. The system depends mainly on recognizing the speaker using the visual speech signal alone. The proposed scheme works in two stages: setting the visual password stage and the verification stage. At the setting stage the visual passwords system request the user to utter a selected password, a video recording of the user face is captured, and processed by a special words-based VSR system which extracts a sequence of feature vectors. In the verification stage, the same procedure is executed, the features will be sent to be compared with the stored visual password. The proposed scheme has been evaluated using a video database of 20 different speakers (10 females and 10 males), and 15 more males in another video database with different experiment sets. The evaluation has proved the system feasibility, with average error rate in the range of 7.63% to 20.51% at the worst tested scenario, and therefore, has potential to be a practical approach with the support of other conventional authentication methods such as the use of usernames and passwords

Visual Speech Recognition

Lip reading is used to understand or interpret speech without hearing it, a technique especially mastered by people with hearing difficulties. The ability to lip read enables a person with a hearing impairment to communicate with others and to engage in social activities, which otherwise would be difficult. Recent advances in the fields of computer vision, pattern recognition, and signal processing has led to a growing interest in automating this challenging task of lip reading. Indeed, automating the human ability to lip read, a process referred to as visual speech recognition (VSR) (or sometimes speech reading), could open the door for other novel related applications. VSR has received a great deal of attention in the last decade for its potential use in applications such as human-computer interaction (HCI), audio-visual speech recognition (AVSR), speaker recognition, talking heads, sign language recognition and video surveillance. Its main aim is to recognise spoken word(s) by using only the visual signal that is produced during speech. Hence, VSR deals with the visual domain of speech and involves image processing, artificial intelligence, object detection, pattern recognition, statistical modelling, etc.Comment: Speech and Language Technologies (Book), Prof. Ivo Ipsic (Ed.), ISBN: 978-953-307-322-4, InTech (2011

TÉCNICAS COMPUTACIONALES PARA LA REDUCCIÓN DEL ESPACIO DE COLOR EN IMÁGENES DIGITALES: UNA REVISIÓN DEL ESTADO DEL ARTE

Las imágenes digitales representadas en modelos RGB almacenan grandes cantidades de información. No obstante, para realizar el procesamiento de estas imágenes se necesitan dispositivos con características especiales. Una estrategia para solventar este inconveniente es realizar una reducción del espacio de color de la imagen sin perder las características esenciales. Existen diferentes técnicas y algoritmos basados en inteligencia computacional, y más concretamente en redes neuronales y lógica difusa, que permiten la reducción del espacio de color en una imagen digital. En este artículo hacemos un análisis del estado del arte de los diferentes algoritmos y técnicas relacionadas con áreas de la inteligencia computacional para la reducción del espacio de color

Lip contour extraction from color images using a deformable model

Abstract The use of visual information from lip movements can improve the accuracy and robustness of a speech recognition system. In this paper, a region-based lip contour extraction algorithm based on deformable model is proposed. The algorithm employs a stochastic cost function to partition a color lip image into lip and non-lip regions such that the joint probability of the two regions is maximized. Given a discrete probability map generated by spatial fuzzy clustering, we show how the optimization of the cost function can be done in the continuous setting. The region-based approach makes the algorithm more tolerant to noise and artifacts in the image. It also allows larger region of attraction, thus making the algorithm less sensitive to initial parameter settings. The algorithm works on unadorned lips and accurate extraction of lip contour is possible.